java.lang.Object
- java.lang.Thread
- - gov.nih.mipav.model.algorithms.AlgorithmBase
  - - gov.nih.mipav.model.algorithms.filters.AlgorithmLaplacian

All Implemented Interfaces:

AlgorithmInterface, java.awt.event.ActionListener, java.awt.event.WindowListener, java.lang.Runnable, java.util.EventListener
```
public class AlgorithmLaplacian
extends AlgorithmBase
implements AlgorithmInterface
```
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. Reference for nonlinear Laplacian operator: "A Nonlinear Laplace Operator as Edge Detector in Noisy Edges" by Lucas J. Van Vliet and Ian T. Young, Computer Vision, Graphics, and Image Processing, Vol. 45, 1989, pp. 167-195.

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 float`	`amplificationFactor`	An amplification factor greater than 1.0 causes this filter to act like a highpass filter.
`private boolean`	`edgeImage`	If true an edge map image should be produced.
`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 float`	`hiThres`	Lower and upper threshold values used in the generation of the edge map.
`private int`	`kernelSize`
`private int[]`	`kExtents`	Dimensionality of the kernel.
`private float`	`loThres`	Lower and upper threshold values used in the generation of the edge map.
`private boolean`	`nonLinear`
`private int`	`operationType`
`private float[]`	`outputBufferX`
`private float[]`	`outputBufferY`
`private float[]`	`outputBufferZ`
`private float[]`	`sigmas`	Standard deviations of the gaussian used to calculate the kernels.
`private static int`	`xOp`
`private static int`	`yOp`
`private static int`	`zOp`
`private ModelImage`	`zXMask`	Mask(unsigned byte) of the zero-crossings of the Laplacian of the gaussian.

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
`AlgorithmLaplacian(ModelImage srcImg, boolean nonLinear, int kernelSize, float[] sigmas, boolean maskFlag, boolean img25D, float ampFactor)`	Constructs a Laplacian algorithm object.
`AlgorithmLaplacian(ModelImage srcImg, float[] sigmas, boolean[] objectBuffer, boolean img25D, float ampFactor)`	Constructs a Laplacian algorithm object.
`AlgorithmLaplacian(ModelImage srcImg, float[] sigmas, boolean maskFlag, boolean img25D, float ampFactor)`	Constructs a Laplacian algorithm object.
`AlgorithmLaplacian(ModelImage destImg, ModelImage srcImg, boolean nonLinear, int kernelSize, float[] sigmas, boolean maskFlag, boolean img25D, float ampFactor)`	Constructs a Laplacian algorithm object.

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
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`	`calcInPlace2D(int nImages)`	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 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.
`static void`	`genLevelMask(int xDim, int yDim, float[] buffer, java.util.BitSet edgeImage, float level)`	Generates a zero crossing mask for a 2D function sets a Bitset object to 1 is a zero crossing is detected.
`private void`	`genZeroXMask(float[] buffer)`	Generates a zero crossing mask for a 2D function sets a ModelImage to 1 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.
`private void`	`runNonLinear()`
`void`	`setEdgeOptions(float loThres, float hiThres)`	Call from dialog if you wish to produce edge image.

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
  - xOp
```
private static final int xOp
```
    See Also:
    
    Constant Field Values
  - yOp
```
private static final int yOp
```
    See Also:
    
    Constant Field Values
  - zOp
```
private static final int zOp
```
    See Also:
    
    Constant Field Values
  - amplificationFactor
```
private float amplificationFactor
```
    An amplification factor greater than 1.0 causes this filter to act like a highpass filter.
  - edgeImage
```
private boolean edgeImage
```
    If true an edge map image should be produced.
  - 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.
  - nonLinear
```
private boolean nonLinear
```
  - kernelSize
```
private int kernelSize
```
  - 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.
  - loThres
```
private float loThres
```
    Lower and upper threshold values used in the generation of the edge map.
  - hiThres
```
private float hiThres
```
    Lower and upper threshold values used in the generation of the edge map.
  - sigmas
```
private float[] sigmas
```
    Standard deviations of the gaussian used to calculate the kernels.
  - zXMask
```
private ModelImage zXMask
```
    Mask(unsigned byte) of the zero-crossings of the Laplacian of the gaussian. Non-zero value indicates edge. Zero in the mask image is background.
  - outputBufferX
```
private float[] outputBufferX
```
  - outputBufferY
```
private float[] outputBufferY
```
  - outputBufferZ
```
private float[] outputBufferZ
```
  - operationType
```
private int operationType
```
- Constructor Detail
  - AlgorithmLaplacian
```
public AlgorithmLaplacian(ModelImage srcImg,
                          float[] sigmas,
                          boolean[] objectBuffer,
                          boolean img25D,
                          float ampFactor)
```
    Constructs a Laplacian algorithm object.
    
    Parameters:
    
    srcImg - source image model
    
    sigmas - Gaussian's standard deviations in the each dimension
    
    objectBuffer - array with true for object, false for background
    
    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.
  - AlgorithmLaplacian
```
public AlgorithmLaplacian(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.
  - AlgorithmLaplacian
```
public AlgorithmLaplacian(ModelImage srcImg,
                          boolean nonLinear,
                          int kernelSize,
                          float[] sigmas,
                          boolean maskFlag,
                          boolean img25D,
                          float ampFactor)
```
    Constructs a Laplacian algorithm object.
    
    Parameters:
    
    srcImg - source image model
    
    nonLinear - If true, use nonlinear Laplacian
    
    kernelSize - Used only with nonlinear Laplacian
    
    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.
  - AlgorithmLaplacian
```
public AlgorithmLaplacian(ModelImage destImg,
                          ModelImage srcImg,
                          boolean nonLinear,
                          int kernelSize,
                          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
    
    nonLinear - If true, use nonlinear Laplacian
    
    kernelSize - Used only with nonlinear Laplacian
    
    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.
- Method Detail
  - genLevelMask
```
public static void genLevelMask(int xDim,
                                int yDim,
                                float[] buffer,
                                java.util.BitSet edgeImage,
                                float level)
```
    Generates a zero crossing mask for a 2D function sets a Bitset object to 1 is a zero crossing is detected.
    
    Parameters:
    
    xDim - X dimension length
    
    yDim - Y dimension length
    
    buffer - array of data in which to find level crossing
    
    edgeImage - edge map of level crossings
    
    level - level of crossings to find (e.g. zero crossing of the Laplacian)
  - finalize
```
public void finalize()
```
    Prepares this class for destruction.
    
    Overrides:
    
    finalize in class AlgorithmBase
  - getZeroXMask
```
public ModelImage getZeroXMask()
```
    Accessor to return mask indicating zero crossings.
    
    Returns:
    
    ModelImage of zero crossings ( 2D function 1 = indicates zero crossing
  - runAlgorithm
```
public void runAlgorithm()
```
    Starts the program.
    
    Specified by:
    
    runAlgorithm in class AlgorithmBase
  - runNonLinear
```
private void runNonLinear()
```
  - setEdgeOptions
```
public void setEdgeOptions(float loThres,
                           float hiThres)
```
    Call from dialog if you wish to produce edge image.
    
    Parameters:
    
    loThres - DOCUMENT ME!
    
    hiThres - DOCUMENT ME!
  - calcInPlace2D
```
private void calcInPlace2D(int nImages)
```
    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.
  - calcInPlace3D
```
private void calcInPlace3D()
```
    Calculates the Laplacian and replaces the source image with the new image.
  - calcStoreInDest2D
```
private void calcStoreInDest2D(int nImages)
```
    This function produces the Laplacian 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.
  - calcStoreInDest3D
```
private void calcStoreInDest3D()
```
    This function produces the Laplacian of input image.
  - genZeroXMask
```
private void genZeroXMask(float[] buffer)
```
    Generates a zero crossing mask for a 2D function sets a ModelImage to 1 if a zero crossing is detected.
    
    Parameters:
    
    buffer - array in which to find zero crossing
  - 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

Class AlgorithmLaplacian

Nested Class Summary

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

Field Summary

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

Fields inherited from class java.lang.Thread

Constructor Summary

Method Summary

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

Methods inherited from class java.lang.Thread

Methods inherited from class java.lang.Object

Field Detail

xOp

yOp

zOp

amplificationFactor

edgeImage

entireImage

nonLinear

kernelSize

GxxData

GyyData

GzzData

kExtents

loThres

hiThres

sigmas

zXMask

outputBufferX

outputBufferY

outputBufferZ

operationType

Constructor Detail

AlgorithmLaplacian

AlgorithmLaplacian

AlgorithmLaplacian

AlgorithmLaplacian

Method Detail

genLevelMask

finalize

getZeroXMask

runAlgorithm

runNonLinear

setEdgeOptions

calcInPlace2D

calcInPlace3D

calcStoreInDest2D

calcStoreInDest3D

genZeroXMask

makeKernels2D

makeKernels3D

algorithmPerformed