Package gov.nih.mipav.model.algorithms

Class AlgorithmLapMedianess

java.lang.Object

java.lang.Thread

gov.nih.mipav.model.algorithms.AlgorithmBase

gov.nih.mipav.model.algorithms.AlgorithmLapMedianess

All Implemented Interfaces:

ActionListener, WindowListener, Runnable, EventListener

public class AlgorithmLapMedianess
extends AlgorithmBase

Calculates the Laplacian of the gaussian of an image at a scale defined by the user.

Version:

0.1 Feb 11, 1998

Author:

Matthew J. McAuliffe, Ph.D.

Nested Class Summary

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

Thread.Builder, Thread.State, Thread.UncaughtExceptionHandler

Field Summary

Fields

Modifier and Type	Field	Description
private float	amplificationFactor	An amplification factor greater than 1.0 causes this filter to act like a highpass filter.
private boolean	entireImage	Flag, if true, indicates that the whole image should be processed.
private float[]	GxxData	Storage location of the second derivative of the Gaussian in the X direction.
private float[]	GyyData	Storage location of the second derivative of the Gaussian in the Y direction.
private float[]	GzzData	Storage location of the second derivative of the Gaussian in the Z direction.
private int[]	kExtents	Dimensionality of the kernel.
private byte[]	sBuffer	Buffer that stores the s value in calcInPlace2DBuffer that contributed to resultBuffer.
private float[]	sigmas	Standard deviations of the gaussian used to calculate the kernels.

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
AlgorithmLapMedianess(ModelImage srcImg, float[] sigmas, boolean maskFlag, boolean img25D, float ampFactor)	Constructs a Laplacian algorithm object.
AlgorithmLapMedianess(ModelImage srcImg, float[] sigmas, boolean maskFlag, boolean img25D, float ampFactor, boolean activeImage)	Constructs a Laplacian algorithm object.
AlgorithmLapMedianess(ModelImage destImg, ModelImage srcImg, float[] sigmas, boolean maskFlag, boolean img25D, float ampFactor)	Constructs a Laplacian algorithm object.
AlgorithmLapMedianess(ModelImage destImg, ModelImage srcImg, float[] sigmas, boolean maskFlag, boolean img25D, float ampFactor, boolean activeImage)	Constructs a Laplacian algorithm object.

Method Summary

Modifier and Type	Method	Description
float[]	calcInBuffer2D(float[] buffer, int[] extents)	Calculates the laplacian medianess of a 2D image and returns it as a float buffer.
private void	calcInPlace2D(int nImages)	Calculates the gradient image and replaces the source image with the new image.
private float[]	calcInPlace2DBuffer(int nImages, float[] buffer, int[] extents)	Calculates the Laplacian image and replaces the source image with the new image.
private void	calcInPlace3D()	Calculates the Laplacian and replaces the source image with the new image.
private float[]	calcInPlace3DBuffer(float[] buffer, int[] extents)	Calculates the Laplacian image and replaces the source image with the new image.
private void	calcStoreInDest2D(int nImages)	This function produces the Laplacian of input image.
private void	calcStoreInDest3D()	This function produces the Laplacian of input image.
void	finalize()	Prepares this class for destruction.
byte[]	getSBuffer()	DOCUMENT ME!
private void	makeKernels2D(float[] sigmas)	Creates Gaussian derivative kernels.
private void	makeKernels3D(float[] sigmas)	Creates Gaussian derivative kernels.
void	runAlgorithm()	Starts the program.

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, isVirtual, join, join, join, join, ofPlatform, ofVirtual, onSpinWait, resume, setContextClassLoader, setDaemon, setDefaultUncaughtExceptionHandler, setName, setPriority, setUncaughtExceptionHandler, sleep, sleep, sleep, start, startVirtualThread, stop, suspend, threadId, toString, yield

Methods inherited from class java.lang.Object

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

Field Details

amplificationFactor

private float amplificationFactor

An amplification factor greater than 1.0 causes this filter to act like a highpass filter.

entireImage

private boolean entireImage

Flag, if true, indicates that the whole image should be processed. If false on process the image over the mask areas.

GxxData

private float[] GxxData

Storage location of the second derivative of the Gaussian in the X direction.

GyyData

private float[] GyyData

Storage location of the second derivative of the Gaussian in the Y direction.

GzzData

private float[] GzzData

Storage location of the second derivative of the Gaussian in the Z direction.

kExtents

private int[] kExtents

Dimensionality of the kernel.

sBuffer

private byte[] sBuffer

Buffer that stores the s value in calcInPlace2DBuffer that contributed to resultBuffer.

sigmas

private float[] sigmas

Standard deviations of the gaussian used to calculate the kernels.

Constructor Details

AlgorithmLapMedianess

public AlgorithmLapMedianess(ModelImage srcImg,
 float[] sigmas,
 boolean maskFlag,
 boolean img25D,
 float ampFactor)

Constructs a Laplacian algorithm object.

Parameters:

srcImg - source image model

sigmas - Gaussian's standard deviations in the each dimension

maskFlag - Flag that indicates that the Laplacian will be calculated for the whole image if equal to true

img25D - Flag, if true, indicates that each slice of the 3D volume should be processed independently. 2D images disregard this flag.

ampFactor - An amplification factor greater than 1.0 causes this filter to act like a highpass filter.

AlgorithmLapMedianess

public AlgorithmLapMedianess(ModelImage srcImg,
 float[] sigmas,
 boolean maskFlag,
 boolean img25D,
 float ampFactor,
 boolean activeImage)

Constructs a Laplacian algorithm object.

Parameters:

srcImg - source image model

sigmas - Gaussian's standard deviations in the each dimension

maskFlag - Flag that indicates that the Laplacian will be calculated for the whole image if equal to true

img25D - Flag, if true, indicates that each slice of the 3D volume should be processed independently. 2D images disregard this flag.

ampFactor - An amplification factor greater than 1.0 causes this filter to act like a highpass filter.

runningInSeparateThread - whether the algorithm is running in a separate thread

AlgorithmLapMedianess

public AlgorithmLapMedianess(ModelImage destImg,
 ModelImage srcImg,
 float[] sigmas,
 boolean maskFlag,
 boolean img25D,
 float ampFactor)

Constructs a Laplacian algorithm object.

Parameters:

destImg - image model where result image is to stored

srcImg - source image model

sigmas - Gaussian's standard deviations in the each dimension

maskFlag - Flag that indicates that the Laplacian will be calculated for the whole image if equal to true

img25D - Flag, if true, indicates that each slice of the 3D volume should be processed independently. 2D images disregard this flag.

ampFactor - An amplification factor greater than 1.0 causes this filter to act like a highpass filter.

AlgorithmLapMedianess

public AlgorithmLapMedianess(ModelImage destImg,
 ModelImage srcImg,
 float[] sigmas,
 boolean maskFlag,
 boolean img25D,
 float ampFactor,
 boolean activeImage)

Constructs a Laplacian algorithm object.

Parameters:

destImg - image model where result image is to stored

srcImg - source image model

sigmas - Gaussian's standard deviations in the each dimension

maskFlag - Flag that indicates that the Laplacian will be calculated for the whole image if equal to true

img25D - Flag, if true, indicates that each slice of the 3D volume should be processed independently. 2D images disregard this flag.

ampFactor - An amplification factor greater than 1.0 causes this filter to act like a highpass filter.

runningInSeparateThread - whether the algorithm is running in a separate thread

Method Details

calcInBuffer2D

public float[] calcInBuffer2D(float[] buffer,
 int[] extents)

Calculates the laplacian medianess of a 2D image and returns it as a float buffer.

Parameters:

buffer - DOCUMENT ME!

extents - DOCUMENT ME!

Returns:

Buffer with the laplacian medianess of the image.

finalize

public void finalize()

Prepares this class for destruction.

Overrides:

finalize in class AlgorithmBase

getSBuffer

public byte[] getSBuffer()

DOCUMENT ME!

Returns:

sBuffer

runAlgorithm

public void runAlgorithm()

Starts the program.

Specified by:

runAlgorithm in class AlgorithmBase

calcInPlace2D

private void calcInPlace2D(int nImages)

Calculates the gradient image and replaces the source image with the new image.

Parameters:

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

calcInPlace2DBuffer

private float[] calcInPlace2DBuffer(int nImages,
 float[] buffer,
 int[] extents)

Calculates the Laplacian image and replaces the source image with the new image.

Parameters:

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

buffer - DOCUMENT ME!

extents - DOCUMENT ME!

Returns:

resultBuffer

calcInPlace3D

private void calcInPlace3D()

Calculates the Laplacian and replaces the source image with the new image.

calcInPlace3DBuffer

private float[] calcInPlace3DBuffer(float[] buffer,
 int[] extents)

Calculates the Laplacian image and replaces the source image with the new image.

Parameters:

buffer - DOCUMENT ME!

extents - DOCUMENT ME!

Returns:

resultBuffer

calcStoreInDest2D

private void calcStoreInDest2D(int nImages)

This function produces the Laplacian of input image. See this Neva

Parameters:

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

calcStoreInDest3D

private void calcStoreInDest3D()

This function produces the Laplacian of input image.

makeKernels2D

private void makeKernels2D(float[] sigmas)

Creates Gaussian derivative kernels.

Parameters:

sigmas - DOCUMENT ME!

makeKernels3D

private void makeKernels3D(float[] sigmas)

Creates Gaussian derivative kernels.

Parameters:

sigmas - DOCUMENT ME!