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

All Implemented Interfaces:

java.awt.event.ActionListener, java.awt.event.WindowListener, java.lang.Runnable, java.util.EventListener
```
public class AlgorithmLocalNormalization
extends AlgorithmBase
```
Local Normalisation equalises colour levels among pixels by removing variations due to lighting; this brings out contrasts in detail.
This is done by normalizing a surface-detail version of an image with its slowly varying local average image. That is to say, each pixel of the output image is the value at that location of the pixel of the high-frequency image divided by the pixel at that same location of the low-frequency image.

The surface-detail image is generated by using an unsharp masking algorithm, and the local average image is a low-pass image generated using a general-purpose (but fast) frequency filter.

References:
1. Local Normalization. http://bigwww.epfl.ch/demo/normalize/desc.html
2. Halyo, Nesim; Rahman, Zia-ur; Park, Stephen. "Information Content in Nonlinear Local Normalization Processing of Digital Images". College of William and Mary. Williamsburg, Virgiana.
See Also:

AlgorithmUnsharpMask, AlgorithmFrequencyFilter

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`	`bChannel`	when true, indicates whether to process the colour channel.
`private AlgorithmFrequencyFilter`	`FFTer`	the AlgorithmFrequencyFilter, to lo-pass filter the image.
`private float`	`frequency`	FrequencyFilter's low-pass cut-off frequency.
`private boolean`	`gChannel`	when true, indicates whether to process the colour channel.
`private boolean`	`is2d`	Images that are solely 2D images set this to true; images with other dimensionality are false.
`private boolean`	`isColourImage`	Colour images set this to true; monochromatic should be false;.
`private int`	`kernelDiameter`	Required by the low pass filter, but is unused with these options.
`private float[]`	`norm`	temporary image-data buffer to store (hi-pass)/(lo-pass) data.
`private boolean`	`rChannel`	when true, indicates whether to process the colour channel.
`private float[]`	`sigmas`	UnsharpMask sigmas, for blurring.
`private ModelImage[]`	`tempImage`	a temporary image array.
`private AlgorithmUnsharpMask`	`unsharper`	the UnsharpMask algorithm, to hi-pass filter the image.
`private double`	`weightingFactor`	UnsharpMask weighting factor.

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
`AlgorithmLocalNormalization(ModelImage dest, ModelImage src, float[] sigmas, double weight, int kernSize, float freq)`	This constructor initialises a Local normalisation algorithm for a source and destination image, and ensures that the destination image is `ModelStorageBase.FLOAT`.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`private void`	`calcInPlace()`	Filters the source image.
`private void`	`calcStoreInDest()`	This function produces a local-normalized image into a ModelImage that does not replace the original image-data.
`private float[]`	`doImageDivision(float[] top, float[] bot)`	takes the data of the two images, one unsharp'd and the other gaussian blur'd, and divides the two pixel-by-pixel to find the locally normalized value for each pixel.
`void`	`finalize()`	Prepares this class for destruction.
`private void`	`normalize()`	works depending on the extent of the image and the colourisation of the source image in question.
`void`	`runAlgorithm()`	Standard algorithm run method.
`void`	`setRGBChannelFilter(boolean r, boolean g, boolean b)`	RGB images are local-normalized by '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
  - FFTer
```
private AlgorithmFrequencyFilter FFTer
```
    the AlgorithmFrequencyFilter, to lo-pass filter the image.
  - frequency
```
private float frequency
```
    FrequencyFilter's low-pass cut-off frequency.
  - is2d
```
private boolean is2d
```
    Images that are solely 2D images set this to true; images with other dimensionality are false.
  - isColourImage
```
private boolean isColourImage
```
    Colour images set this to true; monochromatic should be false;.
  - kernelDiameter
```
private int kernelDiameter
```
    Required by the low pass filter, but is unused with these options.
  - norm
```
private float[] norm
```
    temporary image-data buffer to store (hi-pass)/(lo-pass) data.
  - rChannel
```
private boolean rChannel
```
    when true, indicates whether to process the colour channel.
  - gChannel
```
private boolean gChannel
```
    when true, indicates whether to process the colour channel.
  - bChannel
```
private boolean bChannel
```
    when true, indicates whether to process the colour channel.
  - sigmas
```
private float[] sigmas
```
    UnsharpMask sigmas, for blurring.
  - tempImage
```
private ModelImage[] tempImage
```
    a temporary image array.
  - unsharper
```
private AlgorithmUnsharpMask unsharper
```
    the UnsharpMask algorithm, to hi-pass filter the image.
  - weightingFactor
```
private double weightingFactor
```
    UnsharpMask weighting factor.
- Constructor Detail
  - AlgorithmLocalNormalization
```
public AlgorithmLocalNormalization(ModelImage dest,
                                   ModelImage src,
                                   float[] sigmas,
                                   double weight,
                                   int kernSize,
                                   float freq)
```
    This constructor initialises a Local normalisation algorithm for a source and destination image, and ensures that the destination image is ModelStorageBase.FLOAT.
    Currently (8 May 2003), this algorithm does not support replacing the original data set with that of the locally-normalized image.
    
    Parameters:
    
    dest - DOCUMENT ME!
    
    src - DOCUMENT ME!
    
    sigmas - DOCUMENT ME!
    
    weight - DOCUMENT ME!
    
    kernSize - DOCUMENT ME!
    
    freq - DOCUMENT ME!
- Method Detail
  - finalize
```
public void finalize()
```
    Prepares this class for destruction.
    
    Overrides:
    
    finalize in class AlgorithmBase
  - runAlgorithm
```
public void runAlgorithm()
```
    Standard algorithm run method. It will not run if the source Image is null. The calculation is done and placed in a separate destination image if it is to be stored there.
    
    Specified by:
    
    runAlgorithm in class AlgorithmBase
  - setRGBChannelFilter
```
public void setRGBChannelFilter(boolean r,
                                boolean g,
                                boolean b)
```
    RGB images are local-normalized by 'channel.' That is, each colour, red, blue and green, is filtered independantly of the other two colours. This filter permits selectively filtering any combination of the three channels instead of simply filtering all three. True for any of the arguments enforces filtering that channel.
    
    Parameters:
    
    r - Filter red channel.
    
    g - Filter green channel.
    
    b - Filter blue channel.
  - calcInPlace
```
private void calcInPlace()
```
    Filters the source image. Replaces the original image with the filtered image.
    Does not currently work.
  - calcStoreInDest
```
private void calcStoreInDest()
```
    This function produces a local-normalized image into a ModelImage that does not replace the original image-data.
  - doImageDivision
```
private float[] doImageDivision(float[] top,
                                float[] bot)
```
    takes the data of the two images, one unsharp'd and the other gaussian blur'd, and divides the two pixel-by-pixel to find the locally normalized value for each pixel.
    
    Parameters:
    
    top - DOCUMENT ME!
    
    bot - DOCUMENT ME!
    
    Returns:
    
    DOCUMENT ME!
  - normalize
```
private void normalize()
```
    works depending on the extent of the image and the colourisation of the source image in question.
    calls to doImageDivision(...) for as many slices (and selected colour channels) as necessary to finish off the image.
    
    See Also:
    
    doImageDivision(float[], float[])

Class AlgorithmLocalNormalization

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

FFTer

frequency

is2d

isColourImage

kernelDiameter

norm

rChannel

gChannel

bChannel

sigmas

tempImage

unsharper

weightingFactor

Constructor Detail

AlgorithmLocalNormalization

Method Detail

finalize

runAlgorithm

setRGBChannelFilter

calcInPlace

calcStoreInDest

doImageDivision

normalize