Package gov.nih.mipav.model.algorithms.filters

Class AlgorithmRegularizedIsotropicDiffusion

java.lang.Object

java.lang.Thread

gov.nih.mipav.model.algorithms.AlgorithmBase

gov.nih.mipav.model.algorithms.filters.AlgorithmRegularizedIsotropicDiffusion

All Implemented Interfaces:

java.awt.event.ActionListener, java.awt.event.WindowListener, java.lang.Runnable, java.util.EventListener

public class AlgorithmRegularizedIsotropicDiffusion
extends AlgorithmBase

Algorithm to apply Regularized Isotropic Nonlinear Diffusion as described by:

Joachim Weickert Chapter 15 in Handbook of Computer Vision and Applications, Volume 2 Signal Processing and Pattern Recognition. The book is published by Academic Press, ISBN 0-12-379772-1

Here is a listing of the author's terminology used in the title.

• Regularized the computed image is blurred with a Gaussian kernel prior to taking finite derivatives
• Isotropic the gradient and flux are parallel
• Nonlinear the weights used for combining pixels change over the image, space variant.
• Diffusion this model uses the heat equation

Version:

1.0; 31, July 2003

Author:

Paul F. Hemler, Ph.D.

Nested Class Summary

Nested classes/interfaces inherited from class java.lang.Thread

java.lang.Thread.State, java.lang.Thread.UncaughtExceptionHandler

Field Summary

Fields

Modifier and Type	Field	Description
private AlgorithmSeparableConvolver	algoSepConvolver	Handle to the separable convolution kernel.
private AlgorithmSeparableConvolver	algoSepConvolverB	Handle to the separable convolution kernel.
private AlgorithmSeparableConvolver	algoSepConvolverG	Handle to the separable convolution kernel.
private AlgorithmSeparableConvolver	algoSepConvolverR	Handle to the separable convolution kernel.
private float	contrast	Diffusion contrast parameter.
private boolean	do25D	Flag indicating 2.5D processing.
private float	lambda	Contrast multiplied by the maximum gradient.
(package private) int	numIterations	The number of iterations.
private float[]	sigmas	Standard deviations of the gaussian used to calculate the kernels.
private float	stdDev	Standard deviation used for the Gaussians.
(package private) float	timeStep	The time parameter step size, called tau in the algorithm description In 2D for stability the time step should be <= 0.25.
private float[]	xDataRound	Storage location for the 1D gaussian kernels.
private int	xDim	Image dimensions.
private float[]	yDataRound	Storage location for the 1D gaussian kernels.
private int	yDim	Image dimensions.
private float[]	zDataRound	Storage location for the 1D gaussian kernels.
private int	zDim	Image dimensions.

Fields inherited from class gov.nih.mipav.model.algorithms.AlgorithmBase

destFlag, destImage, image25D, mask, maxProgressValue, minProgressValue, multiThreadingEnabled, nthreads, progress, progressModulus, progressStep, runningInSeparateThread, separable, srcImage, threadStopped

Fields inherited from class java.lang.Thread

MAX_PRIORITY, MIN_PRIORITY, NORM_PRIORITY

Constructor Summary

Constructors

Constructor	Description
AlgorithmRegularizedIsotropicDiffusion(ModelImage destImg, ModelImage srcImg, int numI, float stdDev, float contrast, boolean do25D)	Creates a new AlgorithmRegularizedIsotropicDiffusion object.

Method Summary

Modifier and Type	Method	Description
private float	diffusivity(float d)	Returns the weighting for values used in computing new (diffused) pixel values.
void	finalize()	Prepares this class for destruction.
private float	getVal(float[] buffer, int col, int row)	Returns the value in a 2D image buffer of the pixel at location col, row.
private float	getVal(float[] buffer, int col, int row, int slice)	Returns the value in a 3D image buffer of the pixel at location col, row, slice.
private void	gradientMagnitude(float[] img, float[] mag)	Computes the gradient magnitude of the buffer passed in.
private void	gradientMagnitude3D(float[] img, float[] mag)	Computes the gradient magnitude of the buffer passed in.
private void	makeKernels1D(boolean do3D)	DOCUMENT ME!
private void	run2D(int numImages)	Iterates the Regularized Isotropic Nonlinear Diffusion algorithm for 2D and 2.5D images.
private void	run2DC(int numImages)	Iterates the Regularized Isotropic Nonlinear Diffusion algorithm for 2D and 2.5D color images.
private void	run3D()	Iterates the Regularized Isotropic Nonlinear Diffusion algorithm for 3D images.
private void	run3DC()	Iterates the Regularized Isotropic Nonlinear Diffusion algorithm for 3D color images.
void	runAlgorithm()	Starts the program.
private void	upDateImage(float[] resltBuffer, float[] srcBuffer, float[] gradBuffer)	DOCUMENT ME!
private void	upDateImage3D(float[] resltBuffer, float[] srcBuffer, float[] gradBuffer)	DOCUMENT ME!

Methods inherited from class gov.nih.mipav.model.algorithms.AlgorithmBase

actionPerformed, addListener, addProgressChangeListener, calculateImageSize, calculatePrincipleAxis, computeElapsedTime, computeElapsedTime, convertIntoFloat, delinkProgressToAlgorithm, delinkProgressToAlgorithmMulti, displayError, errorCleanUp, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, generateProgressValues, getDestImage, getElapsedTime, getMask, getMaxProgressValue, getMinProgressValue, getNumberOfThreads, getProgress, getProgressChangeListener, getProgressChangeListeners, getProgressModulus, getProgressStep, getProgressValues, getSrcImage, isCompleted, isImage25D, isMultiThreadingEnabled, isRunningInSeparateThread, isThreadStopped, linkProgressToAlgorithm, linkProgressToAlgorithm, makeProgress, notifyListeners, removeListener, removeProgressChangeListener, run, setCompleted, setImage25D, setMask, setMaxProgressValue, setMinProgressValue, setMultiThreadingEnabled, setNumberOfThreads, setProgress, setProgressModulus, setProgressStep, setProgressValues, setProgressValues, setRunningInSeparateThread, setSrcImage, setStartTime, setThreadStopped, startMethod, windowActivated, windowClosed, windowClosing, windowDeactivated, windowDeiconified, windowIconified, windowOpened

Methods inherited from class java.lang.Thread

activeCount, checkAccess, clone, countStackFrames, currentThread, dumpStack, enumerate, getAllStackTraces, getContextClassLoader, getDefaultUncaughtExceptionHandler, getId, getName, getPriority, getStackTrace, getState, getThreadGroup, getUncaughtExceptionHandler, holdsLock, interrupt, interrupted, isAlive, isDaemon, isInterrupted, join, join, join, onSpinWait, resume, setContextClassLoader, setDaemon, setDefaultUncaughtExceptionHandler, setName, setPriority, setUncaughtExceptionHandler, sleep, sleep, start, stop, suspend, toString, yield

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

numIterations

int numIterations

The number of iterations.

timeStep

float timeStep

The time parameter step size, called tau in the algorithm description In 2D for stability the time step should be <= 0.25. In 3D for stability the time step should be <= 1/6.

algoSepConvolver

private AlgorithmSeparableConvolver algoSepConvolver

Handle to the separable convolution kernel.

algoSepConvolverB

private AlgorithmSeparableConvolver algoSepConvolverB

Handle to the separable convolution kernel.

algoSepConvolverG

private AlgorithmSeparableConvolver algoSepConvolverG

Handle to the separable convolution kernel.

algoSepConvolverR

private AlgorithmSeparableConvolver algoSepConvolverR

Handle to the separable convolution kernel.

contrast

private float contrast

Diffusion contrast parameter.

do25D

private boolean do25D

Flag indicating 2.5D processing.

lambda

private float lambda

Contrast multiplied by the maximum gradient.

sigmas

private float[] sigmas

Standard deviations of the gaussian used to calculate the kernels.

stdDev

private float stdDev

Standard deviation used for the Gaussians.

xDataRound

private float[] xDataRound

Storage location for the 1D gaussian kernels.

xDim

private int xDim

Image dimensions.

yDim

private int yDim

Image dimensions.

zDim

private int zDim

Image dimensions.

yDataRound

private float[] yDataRound

Storage location for the 1D gaussian kernels.

zDataRound

private float[] zDataRound

Storage location for the 1D gaussian kernels.

Constructor Detail

AlgorithmRegularizedIsotropicDiffusion

public AlgorithmRegularizedIsotropicDiffusion(ModelImage destImg,
                                              ModelImage srcImg,
                                              int numI,
                                              float stdDev,
                                              float contrast,
                                              boolean do25D)

Creates a new AlgorithmRegularizedIsotropicDiffusion object.

Parameters:

destImg - ModelImage image model where result image is to stored

srcImg - ModelImage source image model

numI - int number of iterations

stdDev - float standard deviation used in the Gaussians

contrast - float diffusion contrast parameter

do25D - boolean If true, process each slice separately

Method Detail

finalize

public void finalize()

Prepares this class for destruction.

Overrides:

finalize in class AlgorithmBase

runAlgorithm

public void runAlgorithm()

Starts the program.

Specified by:

runAlgorithm in class AlgorithmBase

diffusivity

private float diffusivity(float d)

Returns the weighting for values used in computing new (diffused) pixel values.

Parameters:

d - float Value to compute the diffusivity

Returns:

float The value of the diffusivity corresponding to the d value

getVal

private float getVal(float[] buffer,
                     int col,
                     int row)

Returns the value in a 2D image buffer of the pixel at location col, row.

Parameters:

buffer - float[] The image buffer

col - int Column index

row - int Row index

Returns:

float The pixel value

getVal

private float getVal(float[] buffer,
                     int col,
                     int row,
                     int slice)

Returns the value in a 3D image buffer of the pixel at location col, row, slice.

Parameters:

buffer - float[] The image buffer

col - int Column index

row - int Row index

slice - int Slice index

Returns:

float The pixel value

gradientMagnitude

private void gradientMagnitude(float[] img,
                               float[] mag)

Computes the gradient magnitude of the buffer passed in. This version computes values for the image borders and corners

Parameters:

img - float [] source buffer

mag - float [] a buffer where the gradient magnitude will be placed

gradientMagnitude3D

private void gradientMagnitude3D(float[] img,
                                 float[] mag)

Computes the gradient magnitude of the buffer passed in. This version computes values for the image borders and corners

Parameters:

img - float [] source buffer

mag - float [] a buffer where the gradient magnitude will be placed

makeKernels1D

private void makeKernels1D(boolean do3D)

DOCUMENT ME!

Parameters:

do3D - boolean Flag indicating if a 3D kernel should be computed

run2D

private void run2D(int numImages)

Iterates the Regularized Isotropic Nonlinear Diffusion algorithm for 2D and 2.5D images.

Parameters:

numImages - int number of images to be blurred. If 2D image then nImage = 1, if 3D image where each slice is to processed independently then nImages equals the number of slices in the volume.

run2DC

private void run2DC(int numImages)

Iterates the Regularized Isotropic Nonlinear Diffusion algorithm for 2D and 2.5D color images.

Parameters:

numImages - int number of slices to be blurred. If 2D image then nImage = 1, if 3D image where each slice is to processed independently then nImages equals the number of slices in the volume.

run3D

private void run3D()

Iterates the Regularized Isotropic Nonlinear Diffusion algorithm for 3D images.

run3DC

private void run3DC()

Iterates the Regularized Isotropic Nonlinear Diffusion algorithm for 3D color images.

upDateImage

private void upDateImage(float[] resltBuffer,
                         float[] srcBuffer,
                         float[] gradBuffer)

DOCUMENT ME!

Parameters:

resltBuffer - float [] The preallocated result buffer

srcBuffer - float [] The initialized source buffer containing the input image

gradBuffer - float [] The initialized buffer containing the magnitude of the gradient of the Gaussian blurred input image

upDateImage3D

private void upDateImage3D(float[] resltBuffer,
                           float[] srcBuffer,
                           float[] gradBuffer)

DOCUMENT ME!

Parameters:

resltBuffer - float [] The preallocated result buffer

srcBuffer - float [] The initialized source buffer containing the input image

gradBuffer - float [] The initialized buffer containing the magnitude of the gradient of the Gaussian blurred input image