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

All Implemented Interfaces:

java.awt.event.ActionListener, java.awt.event.WindowListener, java.lang.Runnable, java.util.EventListener
```
public class AlgorithmNonlocalMeansFilter
extends AlgorithmBase
```
This is a port of the 09/03/2006 NLmeansfilter.m and UNLmeansfilter2.m on 02/15/2008 by Jose Vicente Manjon Herrera & Antoni Buades. The code in NLmeansfilter.m is an implementation of the algorithm in the article "A non-local algorithm for image denoising" by Antoni Buades and Jean-Michel Morel. The code in UNLmeansfilter2.m is an implementation of the algortihm in the article "MRI denoising using non-Local Means" by Jose Manjon, Jose Carbonell-Caballero, Juan J. Lull, Gracian Garcia-Marti, Luis Marti-Bonmati, Montserratt Robles, Medical Image Analysis 12 (2008), pp. 514-523. For post processing with Bayes shrink threshold computation: B. K. Shreyamsha Kumar, "Image Denoising based on Non Local-means Filter and its Method Noise Thresholding", Signal, Image and Video Processing, Vol. 7, Issue 6, pp. 1211-1227, 2013. (doi: 10.1007/s11760-012-0389-y) unbiased nonlocal means (value) = sqrt((nonlocal means (value))**2 - 2* sigma**2) For Rician noise standard deviation = sqrt(background mean/2)

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`	`degreeOfFiltering`	Used only with Rician noise filter.
`private boolean`	`do25D`	In 3D if do25D == true, process each slice separately.
`private boolean`	`doBayesShrinkThresholdComputation`
`private boolean`	`doRician`	If true, use unbiased version of NLM to deal with Rician noise in MRI
`private boolean`	`estimateNoiseStandardDeviation`
`private float`	`noiseStandardDeviation`	Noise standard deviation
`private int`	`searchWindowSide`	Side of the learning window of pixels which will be averaged.
`private int`	`similarityWindowSide`	Comparsion window.

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
`AlgorithmNonlocalMeansFilter(ModelImage destImage, ModelImage srcImg, int searchWindowSide, int similarityWindowSide, boolean estimateNoiseStandardDeviation, float noiseStandardDeviation, float degreeOfFiltering, boolean doRician, boolean do25D, boolean doBayesShrinkThresholdComputation)`	Creates a new AlgorithmNonlocalMeans object.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`void`	`finalize()`	Prepares this class for destruction.
`private void`	`run2D()`
`private void`	`run2DRician()`
`private void`	`run3D()`
`private void`	`run3DRician()`
`void`	`runAlgorithm()`	Starts the nonlocal means filter algorithm.

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
  - searchWindowSide
```
private int searchWindowSide
```
    Side of the learning window of pixels which will be averaged. Sizes generally range from about 15 X 15 to 21 X 21.
  - similarityWindowSide
```
private int similarityWindowSide
```
    Comparsion window. This should be smaller than the search window size. In a non-noisy image it can be set to 3 X 3. The value increases with the amount of noise. In general, for noisy images 7 X 7 or 9 X 9 is a good size.
  - estimateNoiseStandardDeviation
```
private boolean estimateNoiseStandardDeviation
```
  - noiseStandardDeviation
```
private float noiseStandardDeviation
```
    Noise standard deviation
  - degreeOfFiltering
```
private float degreeOfFiltering
```
    Used only with Rician noise filter. Should theoretically be around sqrt(2).
  - doRician
```
private boolean doRician
```
    If true, use unbiased version of NLM to deal with Rician noise in MRI
  - do25D
```
private boolean do25D
```
    In 3D if do25D == true, process each slice separately.
  - doBayesShrinkThresholdComputation
```
private boolean doBayesShrinkThresholdComputation
```
- Constructor Detail
  - AlgorithmNonlocalMeansFilter
```
public AlgorithmNonlocalMeansFilter(ModelImage destImage,
                                    ModelImage srcImg,
                                    int searchWindowSide,
                                    int similarityWindowSide,
                                    boolean estimateNoiseStandardDeviation,
                                    float noiseStandardDeviation,
                                    float degreeOfFiltering,
                                    boolean doRician,
                                    boolean do25D,
                                    boolean doBayesShrinkThresholdComputation)
```
    Creates a new AlgorithmNonlocalMeans object.
    
    Parameters:
    
    destImage - denoised image
    
    srcImg - 2D or 3D source image
    
    searchWindowSide - Side of the learning window of pixels which will be averaged
    
    similarityWindowSide - Side of the comparsion window
    
    estimateNoiseStandardDeviation -
    
    noiseStandardDeviation - Noise standard deviation
    
    degreeOfFiltering - degree of filtering - used only for Rician noise filter
    
    do25D - If true, do slice by slice filtering
    
    doBayesShrinkThresholdComputation -
- Method Detail
  - finalize
```
public void finalize()
```
    Prepares this class for destruction.
    
    Overrides:
    
    finalize in class AlgorithmBase
  - runAlgorithm
```
public void runAlgorithm()
```
    Starts the nonlocal means filter algorithm.
    
    Specified by:
    
    runAlgorithm in class AlgorithmBase
  - run2D
```
private void run2D()
```
  - run2DRician
```
private void run2DRician()
```
  - run3D
```
private void run3D()
```
  - run3DRician
```
private void run3DRician()
```

Class AlgorithmNonlocalMeansFilter

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

searchWindowSide

similarityWindowSide

estimateNoiseStandardDeviation

noiseStandardDeviation

degreeOfFiltering

doRician

do25D

doBayesShrinkThresholdComputation

Constructor Detail

AlgorithmNonlocalMeansFilter

Method Detail

finalize

runAlgorithm

run2D

run2DRician

run3D

run3DRician