FloatImage

Constructor Summary
`FloatImage()` Constructs an empty FloatImage
`FloatImage(int w, int h)` Constructs a FloatImage of the size specified
`FloatImage(int w, int h, double[] d)` Constructs a FloatImage of the size specified from a suitably sized array of floats
`FloatImage(int w, int h, float[] d)` Constructs a FloatImage of the size specified from a suitably sized array of floats

Method Summary
`boolean`	`adaptAverage(FloatImage varSquared)` Adapts the average to have the same locally smoothed magnitude as varSquared
`boolean`	`add(float w)` Adds a constant to each pixel
`boolean`	`add(FloatImage fimg)` Adds fimg to this to give this = this + fimg
`boolean`	`add(FloatImage fimg, float w)` Adds a scaled amount of fimg to this to give this = this + w*fimg
`void`	`add(FloatImage fimg1, FloatImage fimg2)` Adds two FloatImages, putting the result in this
`int`	`addToAverage(FloatImage fimg, int n)` Adds an image into this average image
`boolean`	`addToVariance(FloatImage fimg1, FloatImage fimg2, int n)` Adds fimg1 and fimg2 to this complex magnitude average as the real and imaginary parts
`boolean`	`addToVariance(FloatImage fimg1, int n)` Adds fimg1 to the average of absolute values
`boolean`	`addToVarianceSquared(FloatImage fimg1, int n)` Add fimg1 to the average of squared images
`int`	`adjust(FloatImage xshift, FloatImage yshift, FloatImage xtmp, FloatImage ytmp)` Replaces xshift(x,y)=xtmp(x,y) and yshift(x,y)=ytmp(x,y at locations where this(x,y)=0
`static double`	`bytesToDouble(byte[] bytes, int offset)` Convert a byte array into a double
`static float`	`bytesToFloat(byte[] bytes, int offset)` Convert a byte array into a float
`static int`	`bytesToInt(byte[] bytes, int offset)` Converts some bytes into an int
`static long`	`bytesToLong(byte[] bytes, int offset)` Converts some bytes into a long
`static FloatImage[]`	`calculateCurvature(FloatImage[] pmap, int scale)` Calculates the curvature after scaling by the amount indicated
`void`	`classify(FloatImage R, FloatImage G, FloatImage B, FloatImage probCol, FloatImage probColGivenSkin)` Classifies the liklihood of pixels in an image belonging to the class defined by 2 histograms.
`static FloatImage`	`combineUV(FloatImage U, FloatImage V)` Attempts to combine the U and V components to a single channel for skin detection using UU(UU-U/V)(U*U-U/V)
`void`	`convertImage(java.awt.image.BufferedImage bimg)` Converts the given image into this float image, the pixel values are the mean of the r,g,b values
`static void`	`convertImage(java.awt.image.BufferedImage img, FloatImage red, FloatImage green, FloatImage blue)` Converts a BufferedImage into three FloatImages for red, green and blue
`void`	`convertImage(java.awt.Image img)` Converts the given image into this float image, the pixel values are the mean of the r,g,b values
`static boolean`	`convertImage(java.awt.Image img, FloatImage R, FloatImage G, FloatImage B, java.awt.image.ImageObserver ob)` Splits a colour image into 3 FloatImages
`void`	`convertImage(int[] pixels, int w, int h)` Convert the int array (each int is an RGB colour) into an intensity image
`static boolean`	`convertImageHSV(java.awt.Image img, FloatImage H, FloatImage S, FloatImage V, java.awt.image.ImageObserver ob)` Splits a colour image into 3 FloatImages Note: this isn't proper HSV, more like YUV components, with UV converted to polar coords ...
`static boolean`	`convertImageLAB(java.awt.Image img, FloatImage L, FloatImage A, FloatImage B, java.awt.image.ImageObserver ob)` Splits a colour image into 3 (LAB) component FloatImages
`static boolean`	`convertImageRGB(java.awt.Image img, FloatImage R, FloatImage G, FloatImage B, java.awt.image.ImageObserver ob)` Splits a colour image into 3 FloatImages
`static boolean`	`convertImageYUV(java.awt.Image img, FloatImage Y, FloatImage U, FloatImage V, java.awt.image.ImageObserver ob)` Splits a colour image into 3 (YUV) component FloatImages
`static void`	`convertInterleaveImageRGB(java.awt.image.BufferedImage img, FloatImage rgb)` Converts a BufferedImage into one interleaved FloatImages in Red, Green, Blue order
`void`	`convertSubImage(int[] pixels, int width, int height, int x, int y, int w, int h)` Convert the int array (each int is an RGB colour) into an intensity image
`static java.awt.Image`	`convertToImage(FloatImage R, FloatImage G, FloatImage B)` Create a colour image from three float images representing the R, G and B components
`static java.awt.Image`	`convertToImageYUV(FloatImage Y, FloatImage U, FloatImage V)` Create a colour image from three float images representing the Y, U and V components
`void`	`convolve_x(FloatImage fimg, float[] filter, int m, int scale)` Filter this FloatImage in the x direction
`void`	`convolve_x(FloatImage fimg, FloatImage mask, float[] filter, int m, int scale)` Filter this FloatImage in the x direction with masking
`void`	`convolve_y(FloatImage fimg, float[] filter, int m, int scale)` Filter this FloatImage in the y direction
`void`	`convolve_y(FloatImage fimg, FloatImage mask, float[] filter, int m, int scale)` Filter this FloatImage in the y direction with masking
`void`	`convolve(float[] filter, int m, int scale)` Filter the image in the x and y directions (separably) with the filter specified
`void`	`convolve(FloatImage fimg, float[][] filter, int m, int n, int scale)` Non-separable convolution
`void`	`convolve(FloatImage mask, float[] filter, int m, int scale)` Filter the image in the x and y directions (separably) with the filter specified with masking
`void`	`convolve(FloatImage fimg, FloatImage filter, int m, int n, int scale)` Convolve this float image with a filter defined by an image
`boolean`	`convolveFFT(FloatImage fimg1, FloatImage fimg2, boolean inverse)` FFT based convolution, the result is put in this
`FloatImage`	`copy()` Creates and returns a copy of this image
`void`	`copy(FloatImage fimg)` Copy fimg into this
`int`	`correlationFFT(FloatImage fimg1, FloatImage fimg2)` Correlation using FFT, the result is held in this
`static FloatImage`	`createColourHistogram(FloatImage R, FloatImage G, FloatImage B)` Creates a 2D colour histogram (R/(R+G+B), G/(R+G+B)) for an image.
`static FloatImage`	`createColourHistogram(FloatImage R, FloatImage G, FloatImage B, FloatImage mask)` Creates a 2D colour histogram (R/(R+G+B), G/(R+G+B)) for part of an image defines by a mask.
`java.util.ArrayList<KdTreePoint>`	`createTreePoints(FloatImage edges, FloatImage xdir, FloatImage ydir, FloatImage xxdir, FloatImage yydir, FloatImage xydir)` Create an array of kd tree points using pre-selected edge points
`static FloatImage[]`	`deinterleaveImages(FloatImage rgb)` Take an interleaved image, eg.
`static void`	`deinterleaveImages(FloatImage rgb, FloatImage red, FloatImage green, FloatImage blue)`
`boolean`	`divide(FloatImage fimg, float tol)` Divides this image by fimg to give this = this / fimg
`int`	`divide(FloatImage f, FloatImage g)` Pixelwise divide f and g by this and set this to 1 (where this is not zero)
`float`	`dotProduct(FloatImage fimg)` Finds the dot product (aka scalar product or sum of pixel products) of this image with fimg
`float`	`dotProduct(FloatImage fimg, FloatImage mask)` Finds the dot product (aka scalar product or sum of pixel products) of a masked part of this image with fimg
`static void`	`doubleToBytes(double val, byte[] bytes, int offset)` Convert a double into a byte array
`void`	`dual_convolve_x(FloatImage fimg, float[] filter1, float[] filter2, int m1, int m2, int bm)` Convolves in x-direction with two different filters at odd and even pixels respectively
`void`	`dual_convolve_y(FloatImage fimg, float[] filter1, float[] filter2, int m1, int m2, int bm)` Convolves in y-direction with two different filters at odd and even pixels respectively
`void`	`edgeMagnitude(FloatImage dx, FloatImage dy)` Calculates the magnitude of edges
`void`	`edgeWarp(FloatImage dest, MultiscaleWarp shift, int level, int warpType, java.lang.String output)` Non-recursive edge matching
`FloatImage`	`erodeMask()` Perform binary erosion on this FloatImage, any pixels adjacent to zero values are set to zero
`void`	`expand(FloatImage fimg, float[] filter, int m)` Make a double sized version of this and put it in fimg, the filter is used after placing zeros between rows and cols
`void`	`expand(FloatImage fimg, float[] filter, int m, int outW, int outH)` Make a double sized version of this and put it in fimg, the filter is used after placing zeros between rows and cols
`int`	`fillPolygon(java.awt.geom.Point2D.Float[] pts, float[] vals)` Draws a filled polygon on this image with the value v
`int`	`fillPolygon(java.awt.geom.Point2D.Float[] pts, float u, float v)` Draws a filled polygon on this image with the value v
`static float`	`findThreshold(float[] data, float percent)` Attempts to find a suitable threshold on data to keep percentage points
`static void`	`floatToBytes(float val, byte[] bytes, int offset)` Convert a float to a byte array
`static float`	`germanMcClure(FloatImage[] fimg, FloatImage[] av, float d)` Calculates the German-McClure error function between this and fimg using weighting d
`float`	`germanMcClure(FloatImage fimg, float d)` Calculates the German-McClure error function between this and fimg using weighting d
`float`	`get_nocheck(int x, int y)` Gets without checking the bounds
`float`	`get(int i)` Get the ith element of the data array
`float`	`get(int x, int y)` Gets (x,y) and maps values outside the image onto the nearest internal point
`float[]`	`getData()` Get the data vector for this image
`int`	`getHeight()` Get the height of this image
`int`	`getMatchingPoints(FloatImage dest_edge, FloatImage[] sourceData, FloatImage[] destData, java.util.ArrayList<java.awt.geom.Point2D.Float> srcPts, java.util.ArrayList<java.awt.geom.Point2D.Float> dstPts)` Gets two-way matching points
`float`	`getMean()` Gets the mean of this images pixel values
`float[]`	`getMeanAndSD()` Get the mean and standard deviation of this image
`float[]`	`getMeanAndSD(FloatImage mask)` Get the mean and standard deviation of this image
`float[]`	`getMeanAndSD(int x, int y, int w, int h)` Get the mean and standard deviation of a patch of this image
`FloatImage`	`getSubImage(int x, int y, int w, int h)` Gets a sub-part of this image
`int`	`getWidth()` Get the width of this image
`int`	`icpEdgeWarp(FloatImage dest, MultiscaleWarp shift, int minwidth)` Iterative closest point warp
`static FloatImage`	`interleaveImages(FloatImage red, FloatImage green, FloatImage blue)` Turn separate three red green and blue images into one image by interleaving the pixels
`int`	`interpolate(FloatImage xshift, FloatImage yshift, float[] f1, float[] f2, int n1, int n2, int levels, float minJ, int rlevel)` Performs a multiscale interpolation scheme
`static void`	`intToBytes(int val, byte[] bytes, int offset)` Converts an int to a byte array
`void`	`invScale(FloatImage fimg)` Scale each pixel in this image by the inverse of the value of the corresponding pixel in the other image
`static void`	`longToBytes(long val, byte[] bytes, int offset)` Converts a long into a byte array
`void`	`magnitude()` Replaces each pixel with its absolute value
`void`	`magnitudeSquared()` Replaces each pixel with itself squared
`static void`	`main(java.lang.String[] args)` Main method used for testing
`boolean`	`mask(FloatImage maskImg)` Masks this FloatImage
`boolean`	`mask(FloatImage maskImg, float outside)` Masks this FloatImage
`int`	`maxima(FloatImage xdir, FloatImage ydir, FloatImage edges, float thresh)` Find the maxima in the directions given
`java.util.ArrayList<KdTreePoint>`	`maxima(FloatImage xdir, FloatImage ydir, FloatImage xxdir, FloatImage yydir, FloatImage xydir, float thresh)` Create a kd-tree of maxima points using edge information
`int`	`multiEdgeWarp(FloatImage dest, FloatImage[] pmapSrc, FloatImage[] pmapDst, MultiscaleWarp shift, int minwidth, int level)` Multiscale edge based warping with curvature
`int`	`multiEdgeWarp(FloatImage dest, FloatImage xshift, FloatImage yshift)` Edge based warping method
`void`	`multiEdgeWarp(FloatImage dest, MultiscaleWarp shift, int minwidth, int warpType)` Recursive edge matching & warping
`void`	`multiEdgeWarp(FloatImage dest, MultiscaleWarp shift, int minwidth, int level, boolean allscales, int warpType, java.lang.String output)` Recursive edge matching & warping
`boolean`	`multiply(FloatImage fimg)` Mulitplies this image by fimg to give this = this * fimg
`int`	`MultiscaleBlendWaveletMRF_fast2(java.util.ArrayList<FloatImage> source, int count, int lev, Filter H, Filter G, Filter H2, Filter K1, Filter K2, Filter L1, Filter L2)` Blends a set of greyscale images using a multiscale MRF method Algorithm for each source image calculate the low pass version (save for pass to recursive call), calculate the horizontal and vertical wavelet filtered versions, Calculate the low pass version of the input image via recursive call Estimate the horizontal and vertical images using MRF method on wavelet & low pass images Reconstruct image using low-pass and horizontal & vertical wavelets
`void`	`multiscaleOpticFlow(FloatImage target, MultiscaleWarp shift, int minwidth)` Multi scale optical flow method
`int`	`MultiscaleTransformWaveletMRF_fast2(FloatImage original, java.util.ArrayList<FloatImage> source, java.util.ArrayList<FloatImage> target, int lev, Filter H, Filter G, Filter H2, Filter K1, Filter K2, Filter L1, Filter L2)` Algorithm for each source image calculate the low pass version (save for pass to recursive call), calculate the horizontal and vertical wavelet filtered versions, Calculate the low pass version of the input image via recursive call Estimate the horizontal and vertical images using MRF method on wavelet & low pass images Reconstruct image using low-pass and horizontal & vertical wavelets
`float`	`ncc(FloatImage fimg)` Calculates the normalised cross correlation (NCC) with fimg
`float`	`ncc(FloatImage fimg, FloatImage mask)` Calculates the normalised cross correlation (NCC) with fimg using only the masked regions
`float`	`nccPatch(FloatImage fimg, int x, int y)` Calculates the normalised cross correlation (NCC) with fimg
`float[]`	`nccPatchArray(FloatImage fimg)` Calculates the normalised cross correlation (NCC) with fimg
`float`	`nccPatches(FloatImage fimg)` Calculates the normalised cross correlation (NCC) with fimg
`void`	`normalise(float mean, float sd)` Adjusts this image to have the specified mean and s.d.
`void`	`normalise(float mean, float sd, FloatImage mask)` Adjusts this image to have the specified mean and s.d.
`void`	`normalise(FloatImage fimg)` Adjusts this image to have the same mean and s.d.
`void`	`normalise(FloatImage fimg, FloatImage mask)` Adjusts this image to have the same mean and s.d.
`void`	`opticFlow(FloatImage target, MultiscaleWarp shift)` Basic optical flow implementation
`static void`	`quicksort(float[] data, int start, int end)` Quicksort implementation
`void`	`read(java.io.DataInputStream in)` Read a binary format FloatImage from a file
`boolean`	`read(java.lang.String fname)` Read a binary format FloatImage from a file
`int[]`	`reconvertImage()` Creates an int array of colour values from this FloatImage
`static java.awt.image.BufferedImage`	`reconvertImage(FloatImage red, FloatImage green, FloatImage blue)` Converts the red, green and blue colour components into a BufferedImage
`static java.awt.image.BufferedImage`	`reconvertImage(FloatImage red, FloatImage green, FloatImage blue, FloatImage alpha)` Converts the red, green and blue colour components into a BufferedImage
`static java.awt.image.BufferedImage`	`reconvertImageYUV(FloatImage Y, FloatImage U, FloatImage V)` Create a colour image from three float images representing the Y, U and V components
`void`	`reduce(FloatImage fimg, float[] filter, int m)` Make this a shrunken version of fimg by subsampling every other pixel (in x and y) after convolving with filter
`FloatImage`	`reduce(FloatImage fimg, FloatImage mask, float[] filter, int m)` Make this a shrunken version of fimg by subsampling every other pixel (in x and y) after convolving with filter
`void`	`reduce(FloatImage fimg, FloatImage filter, int m)` Make this a shrunken version of fimg by subsampling every other pixel (in x and y) after convolving with filter
`static java.awt.Image`	`reduce(java.awt.Image img, float[] filter, int m)` Make this a shrunken version of img by subsampling every other pixel (in x and y) after convolving with filter
`FloatImage`	`resize(int w, int h)` Resize this image using bilinear resampling to the specified dimensions
`float`	`sample(float x, float y)` Samples (x,y) using bi-linear interpolation
`double`	`sampleAverage()`
`void`	`scale(float w)` Adds a scaled amount of fimg to this i.e.
`void`	`scale(FloatImage fimg)` Scale each pixel in this image by the value of the corresponding pixel in the other image
`void`	`set_nocheck(int i, float v)` Sets (x,y)=v without checking the bounds
`void`	`set_nocheck(int x, int y, float v)` Sets (x,y)=v without checking the bounds
`int`	`set(int x, int y, float v)` Sets (x,y)=v if (x,y) is within the image
`void`	`setSize(int w, int h)` Sets the dimension of the image and reallocates the memory (i.e.
`FloatImage`	`shift(float w, float t)` Creates a scaled and shift version of this image i.e.
`void`	`sqrDifference(FloatImage fimg, FloatImage filter, int m, int n, int scale)` find the square difference between this float image with a filter defined by an image using a windowing technique
`void`	`sqrt()` Fill in the square root of this FloatImage
`void`	`subtract(float val)` Subtract val from each pixel
`boolean`	`subtract(FloatImage fimg)` Subtracts fimg from this i.e.
`static int`	`subtractIgnoreZeros(FloatImage[] current, FloatImage[] fimg)` Subtracts fimg from current i.e.
`double`	`sum()` Return the sum of all pixels in this image
`static float`	`sumError(FloatImage[] fimg, FloatImage[] av)` Calculates the sum error function between this and fimg using weighting d
`static float`	`sumErrorSquared(FloatImage[] fimg, FloatImage[] av)` Calculates the sum squared error function between this and fimg using weighting d
`int`	`threshold(FloatImage edges, float thresh)` Find the points bigger than the threshold
`int`	`thresholdPercent(FloatImage edges, float thresh)` Thresholds the image at a certain percentage of points are kept
`FloatImage`	`transform(float[][] mat, int w, int h)` Perform an affine transform on the image geometry
`int`	`transform(FloatImage src, FloatImage dst, float scale)` Transforms the image by adding (dst-src)*scale
`boolean`	`transformMagnitude(FloatImage var1, FloatImage var2, float shift)` Transforms this by multiplying by var2(x,y)/var1(x,y)^shift
`boolean`	`transformMagSquared(FloatImage var1, FloatImage var2, float shift)` Transforms this by multiplying by var2(x,y)/var1(x,y)^(shift*0.5)
`double[]`	`vectorise(double[] vec)` Converts a FloatImage to a double array
`boolean`	`vectorise(double[] vec, int offset)` Converts a FloatImage to a double array
`static double[]`	`vectorise(FloatImage[] colImg)` Vectorises a colour image stored as 3 FloatImages.
`FloatImage`	`warp(FloatImage xshift, FloatImage yshift, int w, int h)` Warps this using the x and y shifts specified and returns the result as a w by h size image
`FloatImage`	`warpShift(FloatImage xshift, FloatImage yshift, int w, int h)` Warps this using the x and y functions specified and returns the result as a w by h size image
`int`	`weightedTransformMRFHorizontal(FloatImage original, FloatImage this_small, FloatImage original_small, FloatImage magnitude, FloatImage[] source, java.util.ArrayList<FloatImage> source_small, int scount, FloatImage[] target, java.util.ArrayList<FloatImage> target_small, int tcount, double alpha)` MRF transform method
`int`	`weightedTransformMRFVertical(FloatImage original, FloatImage this_small, FloatImage original_small, FloatImage magnitude, FloatImage[] source, java.util.ArrayList<FloatImage> source_small, int scount, FloatImage[] target, java.util.ArrayList<FloatImage> target_small, int tcount, double alpha)` MRF transform method
`void`	`write(java.io.DataOutputStream out)` Write a binary format FloatImage to a DataOutputStream
`boolean`	`write(java.lang.String fname)` Write a binary format FloatImage to a file
`void`	`writeCurvImage(FloatImage[] srcCurv, java.lang.String outfile)` Writes a curvature image to file

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Constructor Detail

FloatImage

public FloatImage()

Constructs an empty FloatImage

FloatImage

public FloatImage(int w,
                  int h)

Constructs a FloatImage of the size specified

Parameters:: w - the width; h - the height

FloatImage

public FloatImage(int w,
                  int h,
                  float[] d)

Constructs a FloatImage of the size specified from a suitably sized array of floats

Parameters:: w - the width; h - the height; d - the array of floating point data

FloatImage

public FloatImage(int w,
                  int h,
                  double[] d)

Constructs a FloatImage of the size specified from a suitably sized array of floats

Parameters:: w - the width; h - the height; d - the array of floating point data

Method Detail

getData

public float[] getData()

Get the data vector for this image

Returns:: returns the data vector of length width by height

getWidth

public int getWidth()

Get the width of this image

Returns:: Return the width of this image

getHeight

public int getHeight()

Get the height of this image

Returns:: The height of this image

get_nocheck

public float get_nocheck(int x,
                         int y)

Gets without checking the bounds

Parameters:: x - coordinate; y - coordinate
Returns:: fimg(x,y)

get

public float get(int x,
                 int y)

Gets (x,y) and maps values outside the image onto the nearest internal point

Parameters:: x - coordinate; y - coordinate
Returns:: fimg(x,y)

get

public float get(int i)

Get the ith element of the data array

Parameters:: i - the element to get
Returns:: returns the ith element of the data array

set_nocheck

public void set_nocheck(int x,
                        int y,
                        float v)

Sets (x,y)=v without checking the bounds

Parameters:: x - coordinate; y - coordinate; v - value

set_nocheck

public void set_nocheck(int i,
                        float v)

Sets (x,y)=v without checking the bounds

Parameters:: i - index in data array; v - value

set

public int set(int x,
               int y,
               float v)

Sets (x,y)=v if (x,y) is within the image

Parameters:: x - coordinate; y - coordinate; v - value
Returns:: 1 if set, 0 if not

sample

public float sample(float x,
                    float y)

Samples (x,y) using bi-linear interpolation

Parameters:: x - coordinate; y - coordinate
Returns:: the sampled value

bytesToFloat

public static float bytesToFloat(byte[] bytes,
                                 int offset)

Convert a byte array into a float

Parameters:: bytes - The array of bytes containgin those to convert; offset - The index in the byte array to start
Returns:: The float value of the bytes

floatToBytes

public static void floatToBytes(float val,
                                byte[] bytes,
                                int offset)

Convert a float to a byte array

Parameters:: val - the value to convert into a byte array; bytes - The array of bytes containgin those to convert; offset - The index in the byte array to start

bytesToDouble

public static double bytesToDouble(byte[] bytes,
                                   int offset)

Convert a byte array into a double

Parameters:: bytes - The array of bytes containgin those to convert; offset - The index in the byte array to start
Returns:: The float value of the bytes

doubleToBytes

public static void doubleToBytes(double val,
                                 byte[] bytes,
                                 int offset)

Convert a double into a byte array

Parameters:: bytes - The array of bytes containgin those to convert; offset - The index in the byte array to start; val - The double value to write

bytesToLong

public static long bytesToLong(byte[] bytes,
                               int offset)

Converts some bytes into a long

Parameters:: bytes - The array of bytes containg those to convert; offset - The index to start at in the byte array
Returns:: The long represented by these bytes

bytesToInt

public static int bytesToInt(byte[] bytes,
                             int offset)

Converts some bytes into an int

Parameters:: bytes - The array of bytes containg those to convert; offset - The index to start at in the byte array
Returns:: The int represented by these bytes

intToBytes

public static void intToBytes(int val,
                              byte[] bytes,
                              int offset)

Converts an int to a byte array

Parameters:: val - The value to convert to a byte array; bytes - The array of bytes containg those to convert; offset - The index to start at in the byte array

longToBytes

public static void longToBytes(long val,
                               byte[] bytes,
                               int offset)

Converts a long into a byte array

Parameters:: val - The value to convert to a byte array; bytes - The array of bytes containg those to convert; offset - The index to start at in the byte array

main

public static void main(java.lang.String[] args)

Main method used for testing

Parameters:: args - The arguments to pass to main

read

public boolean read(java.lang.String fname)

Read a binary format FloatImage from a file

Parameters:: fname - The name of the file to read
Returns:: True if the file was read successfully

read

public void read(java.io.DataInputStream in)
          throws java.io.IOException

Read a binary format FloatImage from a file

Parameters:: in - A dataInputStream opened on the file to read
Throws:: java.io.IOException - thrown if there is an IO problem

write

public void write(java.io.DataOutputStream out)
           throws java.io.IOException

Write a binary format FloatImage to a DataOutputStream

Parameters:: out - The DataOutputSAtream to write to
Throws:: java.io.IOException - thrown if there is an IO problem

write

public boolean write(java.lang.String fname)

Write a binary format FloatImage to a file

Parameters:: fname - The name of the file to read
Returns:: True if the file was read successfully

reduce

public void reduce(FloatImage fimg,
                   float[] filter,
                   int m)

Make this a shrunken version of fimg by subsampling every other pixel (in x and y) after convolving with filter

Parameters:: fimg - The image to shrink; filter - Filter to apply before shrinking; m - the midpoint of the filter

reduce

public void reduce(FloatImage fimg,
                   FloatImage filter,
                   int m)

Make this a shrunken version of fimg by subsampling every other pixel (in x and y) after convolving with filter

Parameters:: fimg - The image to shrink; filter - Filter to apply before shrinking; m - the midpoint of the filter

reduce

public FloatImage reduce(FloatImage fimg,
                         FloatImage mask,
                         float[] filter,
                         int m)

Make this a shrunken version of fimg by subsampling every other pixel (in x and y) after convolving with filter

Parameters:: fimg - The image to shrink; mask - Masking image; filter - Filter to apply before shrinking; m - the midpoint of the filter
Returns:: returns a small version of the mask

reduce

public static java.awt.Image reduce(java.awt.Image img,
                                    float[] filter,
                                    int m)

Make this a shrunken version of img by subsampling every other pixel (in x and y) after convolving with filter

Parameters:: img - The Image to shrink; filter - Filter to apply before shrinking; m - the midpoint of the filter
Returns:: the reduced Image

expand

public void expand(FloatImage fimg,
                   float[] filter,
                   int m)

Make a double sized version of this and put it in fimg, the filter is used after placing zeros between rows and cols

Parameters:: fimg - the destination FloatImage; filter - the upsampling filter coefficeints; m - the filter midpoint

expand

public void expand(FloatImage fimg,
                   float[] filter,
                   int m,
                   int outW,
                   int outH)

Make a double sized version of this and put it in fimg, the filter is used after placing zeros between rows and cols

Parameters:: fimg - the destination FloatImage; filter - the upsampling filter coefficeints; m - the filter midpoint; outW - the output width; outH - the output height

convolve

public void convolve(FloatImage fimg,
                     float[][] filter,
                     int m,
                     int n,
                     int scale)

Non-separable convolution

Parameters:: fimg - the output image, should have same width and height as this; filter - the filter to use; m - the mid-point in x; n - the mid-point in y; scale - the scale factor

convolve

public void convolve(FloatImage fimg,
                     FloatImage filter,
                     int m,
                     int n,
                     int scale)

Convolve this float image with a filter defined by an image

Parameters:: fimg - out image; filter - the filter to convolve with; m - the horizonal midpoint of the filter; n - the vertical midpoint of the filter; scale - the scale factor of the convolution

sqrDifference

public void sqrDifference(FloatImage fimg,
                          FloatImage filter,
                          int m,
                          int n,
                          int scale)

find the square difference between this float image with a filter defined by an image using a windowing technique

Parameters:: fimg - out image; filter - the filter to convolve with; m - the horizonal midpoint of the filter; n - the vertical midpoint of the filter; scale - the scale factor of the convolution

convolve

public void convolve(float[] filter,
                     int m,
                     int scale)

Filter the image in the x and y directions (separably) with the filter specified

Parameters:: filter - The array of values representing the filter; m - The index ofthe mid point of the filter; scale - The amount to dilate the filter (e.g. by placing zeros betwen the coefficients)

convolve_x

public void convolve_x(FloatImage fimg,
                       float[] filter,
                       int m,
                       int scale)

Filter this FloatImage in the x direction

Parameters:: fimg - Stores the output FloatImage; filter - The filter to apply; m - The mid point of the filter; scale - The amount to dilate the filter (e.g. by placing zeros betwen the coefficients)

convolve_y

public void convolve_y(FloatImage fimg,
                       float[] filter,
                       int m,
                       int scale)

Filter this FloatImage in the y direction

Parameters:: fimg - Stores the output FloatImage; filter - The filter to apply; m - The mid point of the filter; scale - The amount to dilate the filter (e.g. by placing zeros betwen the coefficients)

convolve

public void convolve(FloatImage mask,
                     float[] filter,
                     int m,
                     int scale)

Filter the image in the x and y directions (separably) with the filter specified with masking

Parameters:: mask - the mask image to use; filter - The array of values representing the filter; m - The index ofthe mid point of the filter; scale - The amount to dilate the filter (e.g. by placing zeros betwen the coefficients)

convolve_x

public void convolve_x(FloatImage fimg,
                       FloatImage mask,
                       float[] filter,
                       int m,
                       int scale)

Filter this FloatImage in the x direction with masking

Parameters:: fimg - Stores the output FloatImage; mask - the mask image to use; filter - The filter to apply; m - The mid point of the filter; scale - The amount to dilate the filter (e.g. by placing zeros betwen the coefficients)

convolve_y

public void convolve_y(FloatImage fimg,
                       FloatImage mask,
                       float[] filter,
                       int m,
                       int scale)

Filter this FloatImage in the y direction with masking

Parameters:: fimg - Stores the output FloatImage; mask - mask image to use; filter - The filter to apply; m - The mid point of the filter; scale - The amount to dilate the filter (e.g. by placing zeros betwen the coefficients)

erodeMask

public FloatImage erodeMask()

Perform binary erosion on this FloatImage, any pixels adjacent to zero values are set to zero

Returns:: the eroded version of this image

add

public boolean add(FloatImage fimg,
                   float w)

Adds a scaled amount of fimg to this to give this = this + w*fimg

Parameters:: fimg - The FloatImage to add; w - The weight
Returns:: true if added successfully

germanMcClure

public float germanMcClure(FloatImage fimg,
                           float d)

Calculates the German-McClure error function between this and fimg using weighting d

Parameters:: fimg - The FloatImage to compare to; d - The weight
Returns:: error if compared successfully

germanMcClure

public static float germanMcClure(FloatImage[] fimg,
                                  FloatImage[] av,
                                  float d)

Calculates the German-McClure error function between this and fimg using weighting d

Parameters:: fimg - The FloatImage to compare to; av - the (average) image that the error is being measured from; d - The weight
Returns:: error if compared successfully

sumError

public static float sumError(FloatImage[] fimg,
                             FloatImage[] av)

Calculates the sum error function between this and fimg using weighting d

Parameters:: fimg - The FloatImage to compare to; av - the (average) image that the error is being measured from
Returns:: error if compared successfully

sumErrorSquared

public static float sumErrorSquared(FloatImage[] fimg,
                                    FloatImage[] av)

Calculates the sum squared error function between this and fimg using weighting d

Parameters:: fimg - The FloatImage to compare to; av - the (average) image that the error is being measured from
Returns:: error if compared successfully

add

public boolean add(FloatImage fimg)

Adds fimg to this to give this = this + fimg

Parameters:: fimg - The FloatImage to add
Returns:: true if added successfully

add

public void add(FloatImage fimg1,
                FloatImage fimg2)

Adds two FloatImages, putting the result in this

Parameters:: fimg1 - the first image to add; fimg2 - the second image to add

multiply

public boolean multiply(FloatImage fimg)

Mulitplies this image by fimg to give this = this * fimg

Parameters:: fimg - The FloatImage to add
Returns:: true if added successfully

divide

public boolean divide(FloatImage fimg,
                      float tol)

Divides this image by fimg to give this = this / fimg

Parameters:: fimg - The FloatImage to add; tol - values in fimg below tol are not divided
Returns:: true if added successfully

magnitude

public void magnitude()

Replaces each pixel with its absolute value

magnitudeSquared

public void magnitudeSquared()

Replaces each pixel with itself squared

edgeMagnitude

public void edgeMagnitude(FloatImage dx,
                          FloatImage dy)

Calculates the magnitude of edges

Parameters:: dx - the x-derivative image; dy - the y-derivative image

dual_convolve_x

public void dual_convolve_x(FloatImage fimg,
                            float[] filter1,
                            float[] filter2,
                            int m1,
                            int m2,
                            int bm)

Convolves in x-direction with two different filters at odd and even pixels respectively

Parameters:: fimg - the output image; filter1 - the even pixel filter; filter2 - the odd pixel fitler; m1 - the even filter midpoint; m2 - the odd fitler midpoint; bm - the border model

dual_convolve_y

public void dual_convolve_y(FloatImage fimg,
                            float[] filter1,
                            float[] filter2,
                            int m1,
                            int m2,
                            int bm)

Convolves in y-direction with two different filters at odd and even pixels respectively

Parameters:: fimg - the output image; filter1 - the even pixel filter; filter2 - the odd pixel fitler; m1 - the even filter midpoint; m2 - the odd fitler midpoint; bm - the border model

setSize

public void setSize(int w,
                    int h)

Sets the dimension of the image and reallocates the memory (i.e. zeros all pixels)

Parameters:: w - width; h - height

resize

public FloatImage resize(int w,
                         int h)

Resize this image using bilinear resampling to the specified dimensions

Parameters:: w - the desired width; h - the desired height
Returns:: returns the resized version of this

getSubImage

public FloatImage getSubImage(int x,
                              int y,
                              int w,
                              int h)

Gets a sub-part of this image

Parameters:: x - The x-coord; y - the y-coord; w - the output width; h - the output height
Returns:: the sub image from (x, y) of size w by h

mask

public boolean mask(FloatImage maskImg)

Masks this FloatImage

Parameters:: maskImg - Zeros pixels defined by the mask image
Returns:: returns true if the images aer the same size and the mask has been successfully applied

mask

public boolean mask(FloatImage maskImg,
                    float outside)

Masks this FloatImage

Parameters:: maskImg - Zeros pixels defined by the mask image; outside - the constant value to put outside the masked area
Returns:: returns true if the images aer the same size and the mask has been successfully applied

copy

public FloatImage copy()

Creates and returns a copy of this image

Returns:: A copy of this image

copy

public void copy(FloatImage fimg)

Copy fimg into this

Parameters:: fimg - the image to copy

add

public boolean add(float w)

Adds a constant to each pixel

Parameters:: w - The constant to add
Returns:: return true if all goes OK

addToAverage

public int addToAverage(FloatImage fimg,
                        int n)

Adds an image into this average image

Parameters:: fimg - The image to add to this; n - The number of images in the average already
Returns:: Return true if the image was added successfully

adaptAverage

public boolean adaptAverage(FloatImage varSquared)

Adapts the average to have the same locally smoothed magnitude as varSquared

Parameters:: varSquared - the variance squared image
Returns:: true if successful

addToVariance

public boolean addToVariance(FloatImage fimg1,
                             int n)

Adds fimg1 to the average of absolute values

Parameters:: fimg1 - the image to add; n - the number of images added previously
Returns:: true if added successfully, false otherwise

addToVarianceSquared

public boolean addToVarianceSquared(FloatImage fimg1,
                                    int n)

Add fimg1 to the average of squared images

Parameters:: fimg1 - the image to add; n - the number of images previously added to the average
Returns:: true if added successfully

addToVariance

public boolean addToVariance(FloatImage fimg1,
                             FloatImage fimg2,
                             int n)

Adds fimg1 and fimg2 to this complex magnitude average as the real and imaginary parts

Parameters:: fimg1 - the real part to add; fimg2 - the imaginary part to add; n - the number of images previously added to this
Returns:: true if add successfully, false otherwise

transform

public FloatImage transform(float[][] mat,
                            int w,
                            int h)

Perform an affine transform on the image geometry

Parameters:: mat - the transform parameters in a 2 by 3 matrix; w - the output width; h - the output height
Returns:: return the transformed image

transform

public int transform(FloatImage src,
                     FloatImage dst,
                     float scale)

Transforms the image by adding (dst-src)*scale

Parameters:: src - The source image; dst - The destingation image; scale - The amount of transform (0 - no transform, 1 = 100% transform)
Returns:: Return true if the image was transformed successfully (i.e. all images must be same size).

transformMagnitude

public boolean transformMagnitude(FloatImage var1,
                                  FloatImage var2,
                                  float shift)

Transforms this by multiplying by var2(x,y)/var1(x,y)^shift

Parameters:: var1 - the variance of this; var2 - the desired variance; shift - the amount to transform by
Returns:: true if transformed successfully

transformMagSquared

public boolean transformMagSquared(FloatImage var1,
                                   FloatImage var2,
                                   float shift)

Transforms this by multiplying by var2(x,y)/var1(x,y)^(shift*0.5)

Parameters:: var1 - the mag squared of this; var2 - the desired mag squared; shift - the amount to transform by
Returns:: true if transformed successfully

shift

public FloatImage shift(float w,
                        float t)

Creates a scaled and shift version of this image i.e. out = this*t + w

Parameters:: w - The ammount to add to each pixel after scaling; t - The amount to scale this image by
Returns:: The scaled and shifted image

scale

public void scale(float w)

Adds a scaled amount of fimg to this i.e. this = this + w*fimg

Parameters:: w - The weight

scale

public void scale(FloatImage fimg)

Scale each pixel in this image by the value of the corresponding pixel in the other image

Parameters:: fimg - image with scaling values.

invScale

public void invScale(FloatImage fimg)

Scale each pixel in this image by the inverse of the value of the corresponding pixel in the other image

Parameters:: fimg - image with scaling values.

normalise

public void normalise(FloatImage fimg)

Adjusts this image to have the same mean and s.d. as fimg

Parameters:: fimg - The image whose mean and s.d. to copy

normalise

public void normalise(FloatImage fimg,
                      FloatImage mask)

Adjusts this image to have the same mean and s.d. as fimg

Parameters:: fimg - The image whose mean and s.d. to copy; mask - the selection function to use

normalise

public void normalise(float mean,
                      float sd)

Adjusts this image to have the specified mean and s.d.

Parameters:: mean - the desired mean; sd - the desired sd

normalise

public void normalise(float mean,
                      float sd,
                      FloatImage mask)

Adjusts this image to have the specified mean and s.d.

Parameters:: mean - the desired mean; sd - the desired sd; mask - selection function (usually 0 or 1)

getMeanAndSD

public float[] getMeanAndSD()

Get the mean and standard deviation of this image

Returns:: The {mean, s.f.} pair as an array

getMeanAndSD

public float[] getMeanAndSD(int x,
                            int y,
                            int w,
                            int h)

Get the mean and standard deviation of a patch of this image

Parameters:: x - the smallest x coord of the patch; y - the smallest y coord of the patch; w - the width of the patch; h - the height of the patch
Returns:: The {mean, s.f.} pair as an array

getMeanAndSD

public float[] getMeanAndSD(FloatImage mask)

Get the mean and standard deviation of this image

Parameters:: mask - the mask that selects pixels (usually values are 0 or 1)
Returns:: The {mean, s.d.} pair as an array

ncc

public float ncc(FloatImage fimg)

Calculates the normalised cross correlation (NCC) with fimg

Parameters:: fimg - the image to find the NCC with
Returns:: returns the NCC with fimg

nccPatches

public float nccPatches(FloatImage fimg)

Calculates the normalised cross correlation (NCC) with fimg

Parameters:: fimg - the image to find the NCC with
Returns:: returns the NCC with fimg

nccPatchArray

public float[] nccPatchArray(FloatImage fimg)

Calculates the normalised cross correlation (NCC) with fimg

Parameters:: fimg - the image to find the NCC with
Returns:: returns the NCC with fimg

nccPatch

public float nccPatch(FloatImage fimg,
                      int x,
                      int y)

Calculates the normalised cross correlation (NCC) with fimg

Parameters:: fimg - the image to find the NCC with; x - the x coordinate of the location to calculate the ncc at; y - the y coordinate of the location to calculate the ncc at
Returns:: returns the NCC with fimg

ncc

public float ncc(FloatImage fimg,
                 FloatImage mask)

Calculates the normalised cross correlation (NCC) with fimg using only the masked regions

Parameters:: fimg - the image to calulate the NCC with; mask - the mask specifying which image regions to use
Returns:: returns the NCC with fimg in the masked regions

subtract

public boolean subtract(FloatImage fimg)

Subtracts fimg from this i.e. this = this - fimg

Parameters:: fimg - The FloatImage to subtract
Returns:: true if subtracted successfully

sqrt

public void sqrt()

Fill in the square root of this FloatImage

subtractIgnoreZeros

public static int subtractIgnoreZeros(FloatImage[] current,
                                      FloatImage[] fimg)

Subtracts fimg from current i.e. current = current - fimg, except where either current or fimg are black

Parameters:: current - the image to subtract fimg from; fimg - The FloatImage to subtract
Returns:: true if subtracted successfully

convertImageYUV

public static boolean convertImageYUV(java.awt.Image img,
                                      FloatImage Y,
                                      FloatImage U,
                                      FloatImage V,
                                      java.awt.image.ImageObserver ob)

Splits a colour image into 3 (YUV) component FloatImages

Parameters:: img - The image to split; U - The output container for the U component; V - The output container for the V component; Y - The output container for the intensity component; ob - An image observer for img
Returns:: true if successfully converted

convertImageLAB

public static boolean convertImageLAB(java.awt.Image img,
                                      FloatImage L,
                                      FloatImage A,
                                      FloatImage B,
                                      java.awt.image.ImageObserver ob)

Splits a colour image into 3 (LAB) component FloatImages

Parameters:: img - The image to split; L - The output container for the intensity component; A - The output container for the A component; B - The output container for the B component; ob - An image observer for img
Returns:: true if successfully converted

reconvertImageYUV

public static java.awt.image.BufferedImage reconvertImageYUV(FloatImage Y,
                                                             FloatImage U,
                                                             FloatImage V)

Create a colour image from three float images representing the Y, U and V components

Parameters:: Y - The Y (intensity) component; U - The U colour component; V - The V colour component
Returns:: The reconstructed image

convertToImageYUV

public static java.awt.Image convertToImageYUV(FloatImage Y,
                                               FloatImage U,
                                               FloatImage V)

Create a colour image from three float images representing the Y, U and V components

Parameters:: Y - The Y (intensity) component; U - The U colour component; V - The V colour component
Returns:: The reconstructed image

combineUV

public static FloatImage combineUV(FloatImage U,
                                   FloatImage V)

Attempts to combine the U and V components to a single channel for skin detection using U*U*(U*U-U/V)*(U*U-U/V)

Parameters:: U - The U colour component; V - The V colour component
Returns:: The image that combines U and V

createColourHistogram

public static FloatImage createColourHistogram(FloatImage R,
                                               FloatImage G,
                                               FloatImage B,
                                               FloatImage mask)

Creates a 2D colour histogram (R/(R+G+B), G/(R+G+B)) for part of an image defines by a mask.

Parameters:: R - The red component of the image; G - The green component of the image; B - The blue component of the image; mask - The mask that selects which points to include
Returns:: The 2D colour histogram as a FloatImage (to allow easier smoothing etc).

createColourHistogram

public static FloatImage createColourHistogram(FloatImage R,
                                               FloatImage G,
                                               FloatImage B)

Creates a 2D colour histogram (R/(R+G+B), G/(R+G+B)) for an image.

Parameters:: R - The red component of the image; G - The green component of the image; B - The blue component of the image
Returns:: The 2D colour histogram as a FloatImage (to allow easier smoothing etc).

classify

public void classify(FloatImage R,
                     FloatImage G,
                     FloatImage B,
                     FloatImage probCol,
                     FloatImage probColGivenSkin)

Classifies the liklihood of pixels in an image belonging to the class defined by 2 histograms.

Parameters:: R - The red component of the image; G - The green component of the image; B - The blue component of the image; probCol - the 2D histogram of (R/(R+G+B), G/(R+G+B)) colours for the whole image; probColGivenSkin - the 2D histogram of (R/(R+G+B), G/(R+G+B)) colours for the desired object

dotProduct

public float dotProduct(FloatImage fimg)

Finds the dot product (aka scalar product or sum of pixel products) of this image with fimg

Parameters:: fimg - The FloatImage to dot product with
Returns:: Returns the calculated dot propduct

dotProduct

public float dotProduct(FloatImage fimg,
                        FloatImage mask)

Finds the dot product (aka scalar product or sum of pixel products) of a masked part of this image with fimg

Parameters:: mask - The mask to use to select a sub-region; fimg - The FloatImage to dot product with
Returns:: Returns the calculated dot propduct

convertToImage

public static java.awt.Image convertToImage(FloatImage R,
                                            FloatImage G,
                                            FloatImage B)

Create a colour image from three float images representing the R, G and B components

Parameters:: R - The red component; G - The green component; B - The blue component
Returns:: The reconstructed image

convertImageRGB

public static boolean convertImageRGB(java.awt.Image img,
                                      FloatImage R,
                                      FloatImage G,
                                      FloatImage B,
                                      java.awt.image.ImageObserver ob)

Splits a colour image into 3 FloatImages

Parameters:: img - The image to split; R - The output container for the red component; G - The output container for the green component; B - The output container for the blue component; ob - An image observer for img
Returns:: true if successfully converted

convertImage

public static boolean convertImage(java.awt.Image img,
                                   FloatImage R,
                                   FloatImage G,
                                   FloatImage B,
                                   java.awt.image.ImageObserver ob)

Splits a colour image into 3 FloatImages

Parameters:: img - The image to split; R - The output container for the red component; G - The output container for the green component; B - The output container for the blue component; ob - An image observer for img
Returns:: true if successfully converted

convertImage

public static void convertImage(java.awt.image.BufferedImage img,
                                FloatImage red,
                                FloatImage green,
                                FloatImage blue)

Converts a BufferedImage into three FloatImages for red, green and blue

Parameters:: img - The input BufferedImage; red - The output red component; green - The output green component; blue - The output blue component

convertInterleaveImageRGB

public static void convertInterleaveImageRGB(java.awt.image.BufferedImage img,
                                             FloatImage rgb)

Converts a BufferedImage into one interleaved FloatImages in Red, Green, Blue order

Parameters:: img - The input BufferedImage; rgb - The output interleaved components

interleaveImages

public static FloatImage interleaveImages(FloatImage red,
                                          FloatImage green,
                                          FloatImage blue)

Turn separate three red green and blue images into one image by interleaving the pixels

Parameters:: red - the input red part of the image; green - the input green part of the image; blue - the input blue part of the image
Returns:: the interleaved image.

deinterleaveImages

public static FloatImage[] deinterleaveImages(FloatImage rgb)

Take an interleaved image, eg. one produced by interleaveImages and produce the separate rgb images.

Parameters:: rgb - the interleaved image
Returns:: a set of interleaved images

deinterleaveImages

public static void deinterleaveImages(FloatImage rgb,
                                      FloatImage red,
                                      FloatImage green,
                                      FloatImage blue)

reconvertImage

public static java.awt.image.BufferedImage reconvertImage(FloatImage red,
                                                          FloatImage green,
                                                          FloatImage blue)

Converts the red, green and blue colour components into a BufferedImage

Parameters:: red - The input red component; green - The input green component; blue - The input blue component
Returns:: A BufferedImage created from the red, green and blue FloatImages

reconvertImage

public static java.awt.image.BufferedImage reconvertImage(FloatImage red,
                                                          FloatImage green,
                                                          FloatImage blue,
                                                          FloatImage alpha)

Converts the red, green and blue colour components into a BufferedImage

Parameters:: red - The input red component; green - The input green component; blue - The input blue component; alpha - The input blue component
Returns:: A BufferedImage created from the red, green, blue and alpha FloatImages

convertImageHSV

public static boolean convertImageHSV(java.awt.Image img,
                                      FloatImage H,
                                      FloatImage S,
                                      FloatImage V,
                                      java.awt.image.ImageObserver ob)

Splits a colour image into 3 FloatImages Note: this isn't proper HSV, more like YUV components, with UV converted to polar coords ...

Parameters:: img - The image to split; H - The output container for the hue component; S - The output container for the saturation component; V - The output container for the intensity component; ob - An image observer for img
Returns:: true if successfully converted

convertImage

public void convertImage(java.awt.image.BufferedImage bimg)

Converts the given image into this float image, the pixel values are the mean of the r,g,b values

Parameters:: bimg - The image to convert

convertImage

public void convertImage(java.awt.Image img)

Converts the given image into this float image, the pixel values are the mean of the r,g,b values

Parameters:: img - The image to convert

convertImage

public void convertImage(int[] pixels,
                         int w,
                         int h)

Convert the int array (each int is an RGB colour) into an intensity image

Parameters:: pixels - The pixels to convert; w - The width of the input image; h - The height of the input image

convertSubImage

public void convertSubImage(int[] pixels,
                            int width,
                            int height,
                            int x,
                            int y,
                            int w,
                            int h)

Convert the int array (each int is an RGB colour) into an intensity image

Parameters:: x - the x-coord of the sub image rectangle; y - the y-coord of the sub image rectangle; w - the width of the sub image rectangle; h - the height of the sub image rectangle; pixels - The pixels to convert; width - The width of the input image; height - The height of the input image

reconvertImage

public int[] reconvertImage()

Creates an int array of colour values from this FloatImage

Returns:: An array of int values, each one represents an RGB triple

fillPolygon

public int fillPolygon(java.awt.geom.Point2D.Float[] pts,
                       float u,
                       float v)

Draws a filled polygon on this image with the value v

Parameters:: u - The value to write to pixels outside this polygon; pts - The list of points forming the boundary of this polygon; v - The value to write to the pixels inside this polygon
Returns:: 1 if all is OK

fillPolygon

public int fillPolygon(java.awt.geom.Point2D.Float[] pts,
                       float[] vals)

Draws a filled polygon on this image with the value v

Parameters:: vals - The values at the vertices to interpolate; pts - The list of points forming the boundary of this polygon
Returns:: 1 if all is OK

vectorise

public double[] vectorise(double[] vec)

Converts a FloatImage to a double array

Parameters:: vec - the vector in which to place the vectorised image, if it is the wrong size a new vector is created and returned
Returns:: Returns the vectorised image

vectorise

public static double[] vectorise(FloatImage[] colImg)

Vectorises a colour image stored as 3 FloatImages. the vector is in plane order i.e. {r0,r1,r2, ..., rn, g0, g1, ..., gn, b0, b1, ..., bn

Parameters:: colImg - the colour image as an array of 3 FLoatImage
Returns:: a 1D array representing the colour image

vectorise

public boolean vectorise(double[] vec,
                         int offset)

Converts a FloatImage to a double array

Parameters:: vec - The vectorised version of this image; offset - the place to start adding values to the vector
Returns:: true if values are added to the vector OK, false if it failed e.g. if the array is too small

getMean

public float getMean()

Gets the mean of this images pixel values

Returns:: Returns the mean value

subtract

public void subtract(float val)

Subtract val from each pixel

Parameters:: val - the value to subtract

warp

public FloatImage warp(FloatImage xshift,
                       FloatImage yshift,
                       int w,
                       int h)

Warps this using the x and y shifts specified and returns the result as a w by h size image

Parameters:: xshift - the shifts in the x direction; yshift - the shifts in the y direction; w - the output width; h - the output height
Returns:: returns the warped image

warpShift

public FloatImage warpShift(FloatImage xshift,
                            FloatImage yshift,
                            int w,
                            int h)

Warps this using the x and y functions specified and returns the result as a w by h size image

Parameters:: xshift - the locations to sample from in x; yshift - the locations to sample from in y; w - the output width; h - the output height
Returns:: returns the warped image

multiEdgeWarp

public int multiEdgeWarp(FloatImage dest,
                         FloatImage xshift,
                         FloatImage yshift)

Edge based warping method

Parameters:: dest - the target image to warp to; xshift - the x component of the warp; yshift - the y component of the warp
Returns:: return 1, for some reason

multiEdgeWarp

public void multiEdgeWarp(FloatImage dest,
                          MultiscaleWarp shift,
                          int minwidth,
                          int warpType)

Recursive edge matching & warping

Parameters:: dest - target image to warp to; shift - stores the warp function; minwidth - the minimum width to stop the recursion at; warpType - type of twarp to use e.g. full, affine or rigid

multiEdgeWarp

public void multiEdgeWarp(FloatImage dest,
                          MultiscaleWarp shift,
                          int minwidth,
                          int level,
                          boolean allscales,
                          int warpType,
                          java.lang.String output)

Recursive edge matching & warping

Parameters:: dest - target image to warp to; shift - stores the warp function; minwidth - the minimum width to stop the recursion at; level - amount of smoothing to apply; allscales - indicates that matching should be performed at all scales, not just lowest; warpType - type of twarp to use e.g. full, affine or rigid; output - name of output debug image or null

edgeWarp

public void edgeWarp(FloatImage dest,
                     MultiscaleWarp shift,
                     int level,
                     int warpType,
                     java.lang.String output)

Non-recursive edge matching

Parameters:: dest - target image; shift - warp; level - amount of smoothing to apply to the warp; warpType - constant indicating type of warp to use e.g. affine or rigid only, or full; output - name of file to write debugging output image to, or null

writeCurvImage

public void writeCurvImage(FloatImage[] srcCurv,
                           java.lang.String outfile)

Writes a curvature image to file

Parameters:: srcCurv - the 2 curvature componenents, e.g. positive and negative curvature; outfile - the file to write to (as a jpeg)

multiEdgeWarp

public int multiEdgeWarp(FloatImage dest,
                         FloatImage[] pmapSrc,
                         FloatImage[] pmapDst,
                         MultiscaleWarp shift,
                         int minwidth,
                         int level)

Multiscale edge based warping with curvature

Parameters:: dest - the destination image; pmapSrc - the point map of the source surface; pmapDst - the point map of the destination image; shift - the warp to hold the result; minwidth - the smallest size to go in the multiscale pyramid; level - the current level
Returns:: returns 1 for some reason

getMatchingPoints

public int getMatchingPoints(FloatImage dest_edge,
                             FloatImage[] sourceData,
                             FloatImage[] destData,
                             java.util.ArrayList<java.awt.geom.Point2D.Float> srcPts,
                             java.util.ArrayList<java.awt.geom.Point2D.Float> dstPts)

Gets two-way matching points

Parameters:: dest_edge - target edge point image; sourceData - additional source data; destData - additional dest data; srcPts - source point array to add to; dstPts - dest point array to add to
Returns:: returns the number of edges matched

calculateCurvature

public static FloatImage[] calculateCurvature(FloatImage[] pmap,
                                              int scale)

Calculates the curvature after scaling by the amount indicated

Parameters:: pmap - the 3D points in a 3 2D float images; scale - the number of levels to smooth to
Returns:: returns the curvature in the form of an array: {kmxMax, dx[0], dx[1], dx[2], kmnMax, dy[0], dy[1], dy[2]} kmxMax and kmnMax are the points of maximum +ve and -ve curvature dx[0], dy[0] hold the +ve and -ve curvature values (dx[1], dx[2]) and (dy[1], dy[2]) give the directions of principal curvature

threshold

public int threshold(FloatImage edges,
                     float thresh)

Find the points bigger than the threshold

Parameters:: edges - Output image to hold the edge locations (edge = 255, not edge =0); thresh - the threshold value
Returns:: returns 1 for some reason

quicksort

public static void quicksort(float[] data,
                             int start,
                             int end)

Quicksort implementation

Parameters:: data - the data to sort; start - the start of the sub-array to sort; end - the end of the subarray to sort

findThreshold

public static float findThreshold(float[] data,
                                  float percent)

Attempts to find a suitable threshold on data to keep percentage points

Parameters:: data - the data to threshold; percent - the fraction of point you want to keep
Returns:: returns the threshold to use

thresholdPercent

public int thresholdPercent(FloatImage edges,
                            float thresh)

Thresholds the image at a certain percentage of points are kept

Parameters:: edges - output image to keep the location of points > threshold; thresh - the fraction of points to keep
Returns:: returns 1

icpEdgeWarp

public int icpEdgeWarp(FloatImage dest,
                       MultiscaleWarp shift,
                       int minwidth)

Iterative closest point warp

Parameters:: dest - the target float image; shift - holds the output warp function; minwidth - the smallest image width to recurse down to
Returns:: returns 1

maxima

public int maxima(FloatImage xdir,
                  FloatImage ydir,
                  FloatImage edges,
                  float thresh)

Find the maxima in the directions given

Parameters:: xdir - x-direction; ydir - y-direction; edges - holds the output edge locations; thresh - edges whose size is below thresh are ignored
Returns:: returns 1

maxima

public java.util.ArrayList<KdTreePoint> maxima(FloatImage xdir,
                                               FloatImage ydir,
                                               FloatImage xxdir,
                                               FloatImage yydir,
                                               FloatImage xydir,
                                               float thresh)

Create a kd-tree of maxima points using edge information

Parameters:: xdir - x-direction; ydir - y-direction; xxdir - 2nd x derivative; yydir - 2nd y derivative; xydir - 2nd x-y derivative; thresh - threshold on maxima points
Returns:: retuns an array of kd tree points

createTreePoints

public java.util.ArrayList<KdTreePoint> createTreePoints(FloatImage edges,
                                                         FloatImage xdir,
                                                         FloatImage ydir,
                                                         FloatImage xxdir,
                                                         FloatImage yydir,
                                                         FloatImage xydir)

Create an array of kd tree points using pre-selected edge points

Parameters:: edges - contains non-zero values at edge points; xdir - x-direction; ydir - y-direction; xxdir - 2nd x derivative; yydir - 2nd y derivative; xydir - 2nd x-y derivative
Returns:: retuns an array of kd tree points

opticFlow

public void opticFlow(FloatImage target,
                      MultiscaleWarp shift)

Basic optical flow implementation

Parameters:: target - the target image for the flow; shift - the warp

multiscaleOpticFlow

public void multiscaleOpticFlow(FloatImage target,
                                MultiscaleWarp shift,
                                int minwidth)

Multi scale optical flow method

Parameters:: target - target image to flow to; shift - the output warp; minwidth - the smallest width to recurse to

interpolate

public int interpolate(FloatImage xshift,
                       FloatImage yshift,
                       float[] f1,
                       float[] f2,
                       int n1,
                       int n2,
                       int levels,
                       float minJ,
                       int rlevel)

Performs a multiscale interpolation scheme

Parameters:: xshift - output x-shift; yshift - output y-shift; f1 - downsampling filter; f2 - upsampling filter; n1 - length of f1 (port from C); n2 - length of f2 (port from C); levels - number of levels to go to; minJ - not used; rlevel - maximum level to interpolate to, above this just smoothed
Returns:: returns 1

divide

public int divide(FloatImage f,
                  FloatImage g)

Pixelwise divide f and g by this and set this to 1 (where this is not zero)

Parameters:: f - the first image to divide; g - the second image to divide
Returns:: returns 1 if all images are the same size, or zero otherwise

adjust

public int adjust(FloatImage xshift,
                  FloatImage yshift,
                  FloatImage xtmp,
                  FloatImage ytmp)

Replaces xshift(x,y)=xtmp(x,y) and yshift(x,y)=ytmp(x,y at locations where this(x,y)=0

Parameters:: xshift - the x-shift image; yshift - the y-shift image; xtmp - the (low pass) x-shift; ytmp - the (low-pass) y-shift
Returns:: return 0

correlationFFT

public int correlationFFT(FloatImage fimg1,
                          FloatImage fimg2)

Correlation using FFT, the result is held in this

Parameters:: fimg1 - first image; fimg2 - second image
Returns:: returns 0 if different sizes, else 1

convolveFFT

public boolean convolveFFT(FloatImage fimg1,
                           FloatImage fimg2,
                           boolean inverse)

FFT based convolution, the result is put in this

Parameters:: fimg1 - the first input image; fimg2 - the second input image; inverse - flag indicates that inverse onvolution (i.e. deconvolution) should be performed
Returns:: returns true if successful (images same size), false otherwise

MultiscaleBlendWaveletMRF_fast2

public int MultiscaleBlendWaveletMRF_fast2(java.util.ArrayList<FloatImage> source,
                                           int count,
                                           int lev,
                                           Filter H,
                                           Filter G,
                                           Filter H2,
                                           Filter K1,
                                           Filter K2,
                                           Filter L1,
                                           Filter L2)

Blends a set of greyscale images using a multiscale MRF method Algorithm for each source image calculate the low pass version (save for pass to recursive call), calculate the horizontal and vertical wavelet filtered versions, Calculate the low pass version of the input image via recursive call Estimate the horizontal and vertical images using MRF method on wavelet & low pass images Reconstruct image using low-pass and horizontal & vertical wavelets

Parameters:: source - array of images to blend; count - number of images to blend (port from C); lev - level number in pyramid, starting from 0; H - low-pass filter; G - high pass filter; H2 - low pass reconstruction filter; K1 - high pass reconstruction filter; K2 - high pass reconstruction filter; L1 - high pass reconstruction filter; L2 - high pass reconstruction filter
Returns:: returns 1 if successful, 0 otherwise

MultiscaleTransformWaveletMRF_fast2

public int MultiscaleTransformWaveletMRF_fast2(FloatImage original,
                                               java.util.ArrayList<FloatImage> source,
                                               java.util.ArrayList<FloatImage> target,
                                               int lev,
                                               Filter H,
                                               Filter G,
                                               Filter H2,
                                               Filter K1,
                                               Filter K2,
                                               Filter L1,
                                               Filter L2)

Algorithm for each source image calculate the low pass version (save for pass to recursive call), calculate the horizontal and vertical wavelet filtered versions, Calculate the low pass version of the input image via recursive call Estimate the horizontal and vertical images using MRF method on wavelet & low pass images Reconstruct image using low-pass and horizontal & vertical wavelets

Parameters:: original - the original image; source - the set of source group images; target - the set of target group images; lev - the number of levels to build the pyramid; H - the low pass filter; G - the high pass filter; H2 - the reconstructing low pass filter; K1 - the reconstructing high pass filter; K2 - the reconstructing high pass filter; L1 - the reconstructing high pass filter; L2 - the reconstructing high pass filter
Returns:: returns 1 if successful, 0 otherwise

weightedTransformMRFHorizontal

public int weightedTransformMRFHorizontal(FloatImage original,
                                          FloatImage this_small,
                                          FloatImage original_small,
                                          FloatImage magnitude,
                                          FloatImage[] source,
                                          java.util.ArrayList<FloatImage> source_small,
                                          int scount,
                                          FloatImage[] target,
                                          java.util.ArrayList<FloatImage> target_small,
                                          int tcount,
                                          double alpha)

MRF transform method

Parameters:: original - the original to transform; this_small - small version of this; original_small - small version of original; magnitude - float image of wavelet magnitude; source - array of source images; source_small - array of small versions of source images; scount - number of source images; target - array of target images; target_small - array of small target images; tcount - number of target images; alpha - amount to scale the "standard" smoothing width by
Returns:: returns 1

weightedTransformMRFVertical

public int weightedTransformMRFVertical(FloatImage original,
                                        FloatImage this_small,
                                        FloatImage original_small,
                                        FloatImage magnitude,
                                        FloatImage[] source,
                                        java.util.ArrayList<FloatImage> source_small,
                                        int scount,
                                        FloatImage[] target,
                                        java.util.ArrayList<FloatImage> target_small,
                                        int tcount,
                                        double alpha)

MRF transform method

Parameters:: original - the original to transform; this_small - small version of this; original_small - small version of original; magnitude - float image of wavelet magnitude; source - array of source images; source_small - array of small versions of source images; scount - number of source images; target - array of target images; target_small - array of small target images; tcount - number of target images; alpha - amount to scale the "standard" smoothing width by
Returns:: returns 1

sum

public double sum()

Return the sum of all pixels in this image

Returns:: the sum of all pixel values in this image

sampleAverage

public double sampleAverage()

Returns:: the average value of the pixels in this image

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Facemorph Class FloatImage

FloatImage

FloatImage

FloatImage

FloatImage

getData

getWidth

getHeight

get_nocheck

get

get

set_nocheck

set_nocheck

set

sample

bytesToFloat

floatToBytes

bytesToDouble

doubleToBytes

bytesToLong

bytesToInt

intToBytes

longToBytes

main

read

read

write

write

reduce

reduce

reduce

reduce

expand

expand

convolve

convolve

sqrDifference

convolve

convolve_x

convolve_y

convolve

convolve_x

convolve_y

erodeMask

add

germanMcClure

germanMcClure

sumError

sumErrorSquared

add

add

multiply

divide

magnitude

magnitudeSquared

edgeMagnitude

dual_convolve_x

dual_convolve_y

setSize

resize

getSubImage

mask

mask

copy

copy

add

addToAverage

adaptAverage

addToVariance

addToVarianceSquared

addToVariance

transform

transform

transformMagnitude

transformMagSquared

shift

scale

scale

invScale

normalise

Facemorph
Class FloatImage