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

All Implemented Interfaces:

AlgorithmInterface, java.awt.event.ActionListener, java.awt.event.WindowListener, java.lang.Runnable, java.util.EventListener
```
public class AlgorithmGradientMagnitude
extends AlgorithmBase
implements AlgorithmInterface
```
Calculates the gradient magnitude 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
  java.lang.Thread.State, java.lang.Thread.UncaughtExceptionHandler

Field Summary

Fields
Modifier and Type	Field	Description
`private boolean`	`blue`	DOCUMENT ME!
`private boolean`	`entireImage`	Flag, if true, indicates that the whole image should be processed.
`private boolean`	`green`	DOCUMENT ME!
`private float[]`	`Gx2Data`	Storage location of the first derivative of the Gaussian in the X direction for 2D images;
`private float[]`	`GxData`	Storage location of the first derivative of the Gaussian in the X direction.
`private float[]`	`Gy2Data`	Storage location of the first derivative of the Gaussian in the Y direction for 2D images;
`private float[]`	`GyData`	Storage location of the first derivative of the Gaussian in the Y direction.
`private float[]`	`GzData`	Storage location of the first derivative of the Gaussian in the Z direction.
`private int[]`	`kExtents`	Extents of the kernel.
`private float[]`	`outputBuffer`	Receives output of AlgorithmConvolver
`private boolean`	`red`	Flags indicate which color channel to process.
`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
`AlgorithmGradientMagnitude(ModelImage srcImg, float[] sigmas, boolean maskFlag, boolean img25D)`	Creates a new AlgorithmGradientMagnitude object.
`AlgorithmGradientMagnitude(ModelImage destImg, ModelImage srcImg, float[] sigmas, boolean maskFlag, boolean img25D)`	Creates a new AlgorithmGradientMagnitude object.

Method Summary

All 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).
`float[]`	`calcInBuffer2D(float[] buffer, int[] extents, boolean color, float[] xDirs, float[] yDirs)`	Calculates the gradient magnitude of a 2D image and returns it as a float buffer.
`float[]`	`calcInBuffer2DUnnormalized(float[] buffer, int[] extents, boolean color, float[] xDirs, float[] yDirs)`	Calculates the gradient magnitude 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, boolean color, float[] xDirections, float[] yDirections)`	Calculates the gradient image and returns a float buffer with the new values.
`private float[]`	`calcInPlace2DBufferUnnormalized(int nImages, float[] buffer, int[] extents, boolean color, float[] xDirections, float[] yDirections)`	Calculates the gradient image and returns a float buffer with the new values.
`private void`	`calcInPlace34D()`	Calculates the gradient magnitude image and replaces the source image with the new image.
`private void`	`calcStoreInDest2D(int nImages)`	This function produces the gradient magnitude of input image.
`private void`	`calcStoreInDest34D()`	This function produces the gradient magnitude of input image.
`void`	`finalize()`	Prepares this class for destruction.
`private void`	`makeKernels2D()`	Creates Gaussian derivative kernels.
`private void`	`makeKernels3D()`	Creates Gaussian derivative kernels.
`void`	`runAlgorithm()`	Starts the program.
`void`	`setBlue(boolean flag)`	Sets the flag for the blue channel.
`void`	`setGreen(boolean flag)`	Sets the flag for the green channel.
`void`	`setRed(boolean flag)`	Sets the flag for the red channel.

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
  - blue
```
private boolean blue
```
    DOCUMENT ME!
  - entireImage
```
private boolean entireImage
```
    Flag, if true, indicates that the whole image should be processed. If false only process the image over the mask areas.
  - green
```
private boolean green
```
    DOCUMENT ME!
  - Gx2Data
```
private float[] Gx2Data
```
    Storage location of the first derivative of the Gaussian in the X direction for 2D images;
  - GxData
```
private float[] GxData
```
    Storage location of the first derivative of the Gaussian in the X direction.
  - Gy2Data
```
private float[] Gy2Data
```
    Storage location of the first derivative of the Gaussian in the Y direction for 2D images;
  - GyData
```
private float[] GyData
```
    Storage location of the first derivative of the Gaussian in the Y direction.
  - GzData
```
private float[] GzData
```
    Storage location of the first derivative of the Gaussian in the Z direction.
  - kExtents
```
private int[] kExtents
```
    Extents of the kernel.
  - red
```
private boolean red
```
    Flags indicate which color channel to process. True indicates the channel should be processed.
  - sigmas
```
private float[] sigmas
```
    Standard deviations of the gaussian used to calculate the kernels.
  - outputBuffer
```
private float[] outputBuffer
```
    Receives output of AlgorithmConvolver
- Constructor Detail
  - AlgorithmGradientMagnitude
```
public AlgorithmGradientMagnitude(ModelImage srcImg,
                                  float[] sigmas,
                                  boolean maskFlag,
                                  boolean img25D)
```
    Creates a new AlgorithmGradientMagnitude object.
    
    Parameters:
    
    srcImg - source image model
    
    sigmas - Gaussian standard deviations in each dimension
    
    maskFlag - Flag, if true, indicates that the gradient magnitude will be calculated for the whole image
    
    img25D - Flag, if true, indicates that each slice of the 3D volume should be processed independently. 2D images disregard this flag.
  - AlgorithmGradientMagnitude
```
public AlgorithmGradientMagnitude(ModelImage destImg,
                                  ModelImage srcImg,
                                  float[] sigmas,
                                  boolean maskFlag,
                                  boolean img25D)
```
    Creates a new AlgorithmGradientMagnitude object.
    
    Parameters:
    
    destImg - image model where result image is to stored
    
    srcImg - source image model
    
    sigmas - Gaussian standard deviations in each dimension
    
    maskFlag - Flag, if true, indicates that the gradient magnitude will be calculated for the whole image
    
    img25D - Flag, if true, indicates that each slice of the 3D volume should be processed independently. 2D images disregard this flag.
- Method Detail
  - calcInBuffer2D
```
public float[] calcInBuffer2D(float[] buffer,
                              int[] extents,
                              boolean color,
                              float[] xDirs,
                              float[] yDirs)
```
    Calculates the gradient magnitude of a 2D image and returns it as a float buffer.
    
    Parameters:
    
    buffer - DOCUMENT ME!
    
    extents - DOCUMENT ME!
    
    color - DOCUMENT ME!
    
    xDirs - DOCUMENT ME!
    
    yDirs - DOCUMENT ME!
    
    Returns:
    
    Buffer with the gradient magnitude of the image.
  - calcInBuffer2DUnnormalized
```
public float[] calcInBuffer2DUnnormalized(float[] buffer,
                                          int[] extents,
                                          boolean color,
                                          float[] xDirs,
                                          float[] yDirs)
```
    Calculates the gradient magnitude of a 2D image and returns it as a float buffer.
    
    Parameters:
    
    buffer - DOCUMENT ME!
    
    extents - DOCUMENT ME!
    
    color - DOCUMENT ME!
    
    xDirs - DOCUMENT ME!
    
    yDirs - DOCUMENT ME!
    
    Returns:
    
    Buffer with the gradient magnitude of the image.
  - 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
  - setBlue
```
public void setBlue(boolean flag)
```
    Sets the flag for the blue channel.
    
    Parameters:
    
    flag - if set to true then the blue channel is processed.
  - setGreen
```
public void setGreen(boolean flag)
```
    Sets the flag for the green channel.
    
    Parameters:
    
    flag - if set to true then the green channel is processed.
  - setRed
```
public void setRed(boolean flag)
```
    Sets the flag for the red channel.
    
    Parameters:
    
    flag - if set to true then the red channel is processed.
  - calcInPlace2D
```
private void calcInPlace2D(int nImages)
```
    Calculates the gradient image and replaces the source image with the new image.
    
    Parameters:
    
    nImages - number of images on which to calculate the gradient magnitude. 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,
                                    boolean color,
                                    float[] xDirections,
                                    float[] yDirections)
```
    Calculates the gradient image and returns a float buffer with the new values.
    
    Parameters:
    
    nImages - number of images on which to calculate the gradient magnitude. 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!
    
    color - DOCUMENT ME!
    
    xDirections - DOCUMENT ME!
    
    yDirections - DOCUMENT ME!
    
    Returns:
    
    DOCUMENT ME!
  - calcInPlace2DBufferUnnormalized
```
private float[] calcInPlace2DBufferUnnormalized(int nImages,
                                                float[] buffer,
                                                int[] extents,
                                                boolean color,
                                                float[] xDirections,
                                                float[] yDirections)
```
    Calculates the gradient image and returns a float buffer with the new values.
    
    Parameters:
    
    nImages - number of images on which to calculate the gradient magnitude. 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!
    
    color - DOCUMENT ME!
    
    xDirections - DOCUMENT ME!
    
    yDirections - DOCUMENT ME!
    
    Returns:
    
    DOCUMENT ME!
  - calcInPlace34D
```
private void calcInPlace34D()
```
    Calculates the gradient magnitude image and replaces the source image with the new image.
  - calcStoreInDest2D
```
private void calcStoreInDest2D(int nImages)
```
    This function produces the gradient magnitude of input image.
    
    Parameters:
    
    nImages - number of images on which to calculate the gradient magnitude. 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.
  - calcStoreInDest34D
```
private void calcStoreInDest34D()
```
    This function produces the gradient magnitude of input image.
  - 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 AlgorithmGradientMagnitude

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

blue

entireImage

green

Gx2Data

GxData

Gy2Data

GyData

GzData

kExtents

red

sigmas

outputBuffer

Constructor Detail

AlgorithmGradientMagnitude

AlgorithmGradientMagnitude

Method Detail

calcInBuffer2D

calcInBuffer2DUnnormalized

finalize

runAlgorithm

setBlue

setGreen

setRed

calcInPlace2D

calcInPlace2DBuffer

calcInPlace2DBufferUnnormalized

calcInPlace34D

calcStoreInDest2D

calcStoreInDest34D

makeKernels2D

makeKernels3D

algorithmPerformed