Package gov.nih.mipav.model.algorithms

Class AlgorithmEdgeNMSuppression

java.lang.Object

java.lang.Thread

gov.nih.mipav.model.algorithms.AlgorithmBase

gov.nih.mipav.model.algorithms.AlgorithmEdgeNMSuppression

All Implemented Interfaces:

AlgorithmInterface, ActionListener, WindowListener, Runnable, EventListener

public class AlgorithmEdgeNMSuppression
extends AlgorithmBase
implements AlgorithmInterface

Calculates the non-maximum suppression of an image at a scale defined by the user. This algorithm produces an edge map of the zero crossings of the non-maximum suppression for 2D images and 2.5D images. Edges are defined as the union of points for which the gradient magnitude assumes a maximum in the gradient direction. Introuduce a local orthonormal coordinate system (u,v) at any point P0, where the v-axis is parallel to the gradient direction at P0, and the u-axis is perpindicular. Iu = sin(a)*Ix - cos(a)*Iy Iv = cos(a)*Ix + sin(a)*Iy cos(a) = Ix/(sqrt(Ix*Ix + Iy*Iy)) evaluated at P0 sin(a) = Iy/(sqrt(Ix*Ix + Iy*Iy)) evaluated at P0 Iu = (Ix*Iy - Ix*Iy)/(sqrt(Ix*Ix + Iy*Iy)) = 0 Iv = (Ix*Ix + Iy*Iy)/(sqrt(Ix*Ix + Iy*Iy)) = sqrt(Ix*Ix + Iy*Iy) Iv*Iv = Ix*Ix + Iy*Iy Ivv = (cos(a)*Ix + sin(a)*Iy)(cos(a)*Ix + sin(a)*Iy) = cos(a)*cos(a)*Ixx + 2*cos(a)*sin(a)*Ixy + sin(a)*sin(a)*Iyy = (Ix*Ix*Ixx + 2*Ix*Iy*Ixy + Iy*Iy*Iyy)/(Ix*Ix + Iy*Iy) Iv*Iv*Ivv = Ix*Ix*Ixx + 2*Ix*Iy*Ixy + Iy*Iy*Iyy Ivvv = (cos(a)*cos(a)*Ixx + 2*cos(a)*sin(a)*Ixy + sin(a)*sin(a)*Iyy)(cos(a)*Ix + sin(a)*Iy) = cos(a)*cos(a)*cos(a)*Ixxx + 3*cos(a)*cos(a)*sin(a)*Ixxy + 3*cos(a)*sin(a)*sin(a)*Ixyy + sin(a)*sin(a)*sin(a)*Iyyy = (Ix*Ix*Ix*Ixxx + 3*Ix*Ix*Iy*Ixxy + 3*Ix*Iy*Iy*Ixyy + Iy*Iy*Iy*Iyyy)/((Ix*Ix + Iy*Iy)**3/2) Iv*Iv*Iv*Ivvv = Ix*Ix*Ix*Ixxx + 3*Ix*Ix*Iy*Ixxy + 3*Ix*Iy*Iy*Ixyy + Iy*Iy*Iy*Iyyy Assuming that the second and third-order directional derivatives of I in the v-direction are not simultaneously zero, a necessary and sufficient condition for P0 to be a gradient maximum in the gradient direction may be stated as: Ivv = 0, Ivvv invalid input: '<' 0. Since only the sign information is important, this condition can be restated as: Iv*Iv*Ivv = 0, Iv*Iv*Iv*Ivvv invalid input: '<' 0. Reference: Geometry-Driven Diffusion in Computer Vision, Bart M. ter Haar Romeny(Ed.), Chapter2:Linear Scale-Space II: Early Visual Operations by Tony Lindeberg and Bart M. ter Haar Romeny, Kluwer Academic Publishers, 1994, page 45.

For 3D a similar derivation: Iv = cos(a)*sin(b)*Ix + sin(a)*sin(b)*Iy + cos(b)*Iz where spherical coordinates are being used cos(a) = Ix/(sqrt(Ix*Ix + Iy*Iy)) evaluated at P0 sin(a) = Iy/(sqrt(Ix*Ix + Iy*Iy)) evaluated at P0 cos(b) = Iz/(sqrt(Ix*Ix + Iy*Iy + Iz*Iz)) evaluated at P0 sin(b) = sqrt(Ix*Ix + Iy*Iy)/(sqrt(Ix*Ix + Iy*Iy + Iz*Iz)) evaluated at P0 Iv = (Ix*Ix + Iy*Iy + Iz*Iz)/(sqrt(Ix*Ix + Iy*Iy + Iz*Iz)) = sqrt(Ix*Ix + Iy*Iy + Iz*Iz) Iv*Iv = Ix*Ix + Iy*Iy + Iz*Iz Ivv = (cos(a)*sin(b)*Ix + sin(a)*sin(b)*Iy + cos(b)*Iz)(cos(a)*sin(b)*Ix + sin(a)*sin(b)*Iy + cos(b)*Iz) = cos(a)*cos(a)*sin(b)*sin(b)*Ixx + 2*cos(a)*sin(a)*sin(b)*sin(b)*Ixy + 2*cos(a)*cos(b)*sin(b)*Ixz + sin(a)*sin(a)*sin(b)*sin(b)*Iyy + 2*sin(a)*cos(b)*sin(b)*Iyz + cos(b)*cos(b)*Izz = (Ix*Ix*Ixx + 2*Ix*Iy*Ixy + 2*Ix*Iz*Ixz + Iy*Iy*Iyy + 2*Iy*Iz*Iyz + Iz*Iz*Izz)/ (Ix*Ix + Iy*Iy + Iz*Iz) Iv*Iv*Ivv = Ix*Ix*Ixx + 2*Ix*Iy*Ixy + 2*Ix*Iz*Ixz + Iy*Iy*Iyy + 2*Iy*Iz*Iyz + Iz*Iz*Izz Ivvv = (cos(a)*cos(a)*sin(b)*sin(b)*Ixx + 2*cos(a)*sin(a)*sin(b)*sin(b)*Ixy + 2*cos(a)*cos(b)*sin(b)*Ixz + sin(a)*sin(a)*sin(b)*sin(b)*Iyy + 2*sin(a)*cos(b)*sin(b)*Iyz + cos(b)*cos(b)*Izz)(cos(a)*sin(b)*Ix + sin(a)*sin(b)*Iy + cos(b)*Iz) = cos(a)*cos(a)*cos(a)*sin(b)*sin(b)*sin(b)*Ixxx + 3*cos(a)*cos(a)*sin(a)*sin(b)*sin(b)*sin(b)*Ixxy + 3*cos(a)*cos(a)*cos(b)*sin(b)*sin(b)*Ixxz + 3*cos(a)*sin(a)*sin(a)*sin(b)*sin(b)*sin(b)*Ixyy + 6*cos(a)*sin(a)*cos(b)*sin(b)*sin(b)*Ixyz + 3*cos(a)*cos(b)*cos(b)*sin(b)*Ixzz + sin(a)*sin(a)*sin(a)*sin(b)*sin(b)*sin(b)*Iyyy + 3*sin(a)*sin(a)*cos(b)*sin(b)*sin(b)*Iyyz + 3*sin(a)*cos(b)*cos(b)*sin(b)*Iyzz + cos(b)*cos(b)*cos(b)*Izzz = (Ix*Ix*Ix*Ixxx + 3*Ix*Ix*Iy*Ixxy + 3*Ix*Ix*Iz*Ixxz + 3*Ix*Iy*Iy*Ixyy + 6*Ix*Iy*Iz*Ixyz + 3*Ix*Iz*Iz*Ixzz + Iy*Iy*Iy*Iyyy + 3*Iy*Iy*Iz*Iyyz + 3*Iy*Iz*Iz*Iyzz + Iz*Iz*Iz*Izzz)/ ((Ix*Ix + Iy*Iy + Iz*Iz)**1.5) Iv*Iv*Iv*Ivvv = Ix*Ix*Ix*Ixxx + 3*Ix*Ix*Iy*Ixxy + 3*Ix*Ix*Iz*Ixxz + 3*Ix*Iy*Iy*Ixyy + 6*Ix*Iy*Iz*Ixyz + 3*Ix*Iz*Iz*Ixzz + Iy*Iy*Iy*Iyyy + 3*Iy*Iy*Iz*Iyyz + 3*Iy*Iz*Iz*Iyzz + Iz*Iz*Iz*Izzz

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 boolean	entireImage	DOCUMENT ME!
private float[]	GxData	DOCUMENT ME!
private float[]	GxxData	DOCUMENT ME!
private float[]	GxxxData	DOCUMENT ME!
private float[]	GxxyData	DOCUMENT ME!
private float[]	GxxzData	DOCUMENT ME!
private float[]	GxyData	DOCUMENT ME!
private float[]	GxyyData	DOCUMENT ME!
private float[]	GxyzData	DOCUMENT ME!
private float[]	GxzData	DOCUMENT ME!
private float[]	GxzzData	DOCUMENT ME!
private float[]	GyData	DOCUMENT ME!
private float[]	GyyData	DOCUMENT ME!
private float[]	GyyyData	DOCUMENT ME!
private float[]	GyyzData	DOCUMENT ME!
private float[]	GyzData	DOCUMENT ME!
private float[]	GyzzData	DOCUMENT ME!
private float[]	GzData	DOCUMENT ME!
private float[]	GzzData	DOCUMENT ME!
private float[]	GzzzData	DOCUMENT ME!
private int[]	kExtents	DOCUMENT ME!
static final int	MARCHING_SQUARES	Perform zero crossing detection using the marching squares method.
static final int	OLD_DETECTION	Perform zero crossing detection using Matt's old method.
private float[]	outputBuffer
private float[]	sigmas	DOCUMENT ME!
private int	zeroDetectionType	The type of zero crossing detection to use.
private ModelImage	zXMask	DOCUMENT ME!

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
AlgorithmEdgeNMSuppression(ModelImage destImg, ModelImage srcImg, float[] sigmas, boolean maskFlag, boolean img25D)	Creates a new AlgorithmEdgeNMSuppression object.

Method Summary

Modifier and Type	Method	Description
void	algorithmPerformed(AlgorithmBase algorithm)	Called after an algorithm this listener is registered to exits (maybe successfully, maybe not).
private void	calcStoreInDest2D(int nImages, int detectionType)	This function produces the EdgeNMSup of input image.
private void	calcStoreInDest3D(int detectionType)	This function produces the Non-maximum suppression of input image.
void	finalize()	Prepares this class for destruction.
static BitSet	genLevelMask(int xDim, int yDim, float[] buffer, float level, int detectionType)	Generates a zero crossing mask for a 2D function sets a Bitset object to 1 is a zero crossing is detected.
void	genZeroXMask(int slice, float[] buffer, float[] buffer2, int detectionType)	Generates a zero crossing mask for a 2D function sets a ModelImage to 255 if a zero crossing is detected.
ModelImage	getZeroXMask()	Accessor to return mask indicating zero crossings.
private void	makeKernels2D()	Creates Gaussian derivative kernels.
private void	makeKernels3D()	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

MARCHING_SQUARES

public static final int MARCHING_SQUARES

Perform zero crossing detection using the marching squares method.

See Also:

• Constant Field Values

OLD_DETECTION

public static final int OLD_DETECTION

Perform zero crossing detection using Matt's old method.

See Also:

• Constant Field Values

entireImage

private boolean entireImage

DOCUMENT ME!

GxData

private float[] GxData

DOCUMENT ME!

GxxData

private float[] GxxData

DOCUMENT ME!

GxxxData

private float[] GxxxData

DOCUMENT ME!

GxxyData

private float[] GxxyData

DOCUMENT ME!

GxxzData

private float[] GxxzData

DOCUMENT ME!

GxyData

private float[] GxyData

DOCUMENT ME!

GxyyData

private float[] GxyyData

DOCUMENT ME!

GxyzData

private float[] GxyzData

DOCUMENT ME!

GxzData

private float[] GxzData

DOCUMENT ME!

GxzzData

private float[] GxzzData

DOCUMENT ME!

GyData

private float[] GyData

DOCUMENT ME!

GyyData

private float[] GyyData

DOCUMENT ME!

GyyyData

private float[] GyyyData

DOCUMENT ME!

GyyzData

private float[] GyyzData

DOCUMENT ME!

GyzData

private float[] GyzData

DOCUMENT ME!

GyzzData

private float[] GyzzData

DOCUMENT ME!

GzData

private float[] GzData

DOCUMENT ME!

GzzData

private float[] GzzData

DOCUMENT ME!

GzzzData

private float[] GzzzData

DOCUMENT ME!

kExtents

private int[] kExtents

DOCUMENT ME!

sigmas

private float[] sigmas

DOCUMENT ME!

zeroDetectionType

private int zeroDetectionType

The type of zero crossing detection to use.

zXMask

private ModelImage zXMask

DOCUMENT ME!

outputBuffer

private float[] outputBuffer

Constructor Details

AlgorithmEdgeNMSuppression

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

Creates a new AlgorithmEdgeNMSuppression 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 EdgeNMSup 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.

Method Details

genLevelMask

public static BitSet genLevelMask(int xDim,
 int yDim,
 float[] buffer,
 float level,
 int detectionType)

Generates a zero crossing mask for a 2D function sets a Bitset object to 1 is a zero crossing is detected.

Parameters:

xDim - the buffer's x dimension

yDim - the buffer's y dimension

buffer - array in which to find zero crossing

level - the level to find the crossing of (usually will be 0)

detectionType - the type of zero crossing method to use

Returns:

DOCUMENT ME!

finalize

public void finalize()

Prepares this class for destruction.

Overrides:

finalize in class AlgorithmBase

genZeroXMask

public void genZeroXMask(int slice,
 float[] buffer,
 float[] buffer2,
 int detectionType)

Generates a zero crossing mask for a 2D function sets a ModelImage to 255 if a zero crossing is detected.

Parameters:

slice - DOCUMENT ME!

buffer - array in which to find zero crossing

buffer2 - array which ensures that zero crossing is only counted if buffer2 value at that position is less than zero

detectionType - the type of zero crossing detection to perform

getZeroXMask

public ModelImage getZeroXMask()

Accessor to return mask indicating zero crossings.

Returns:

ModelImage of zero crossings (2D function); 255 = indicates zero crossing

runAlgorithm

public void runAlgorithm()

Starts the program.

Specified by:

runAlgorithm in class AlgorithmBase

calcStoreInDest2D

private void calcStoreInDest2D(int nImages,
 int detectionType)

This function produces the EdgeNMSup of input 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.

detectionType - the type of zero crossing detection to perform

calcStoreInDest3D

private void calcStoreInDest3D(int detectionType)

This function produces the Non-maximum suppression of input image.

Parameters:

detectionType - the type of zero crossing detection to perform

makeKernels2D

private void makeKernels2D()

Creates Gaussian derivative kernels.

makeKernels3D

private void makeKernels3D()

Creates Gaussian derivative kernels.

algorithmPerformed

public void algorithmPerformed(AlgorithmBase algorithm)

Description copied from interface: AlgorithmInterface

Called after an algorithm this listener is registered to exits (maybe successfully, maybe not). If the algorithm is run in a separate thread, this call will be made within that thread. If not, this call will be made from that same, shared thread.

Specified by:

algorithmPerformed in interface AlgorithmInterface

Parameters:

algorithm - the algorithm which has just completed