trainableSegmentation.filters

Class Kuwahara

java.lang.Object

trainableSegmentation.filters.Kuwahara

All Implemented Interfaces:

ij.plugin.filter.PlugInFilter

public class Kuwahara
extends Object
implements ij.plugin.filter.PlugInFilter

A version of the Kuwahara filter that uses linear kernels rather than square ones. This plugin is licensed under the GNU Public License v2 or later.

Author:

Christian Tischer

Field Summary

Fields

Modifier and Type	Field and Description
protected int	imH
protected int	imW
protected int	kH
protected int	kW
protected int	nAngles
protected boolean	showKernels
protected int	size
static int	VARIANCE
static int	VARIANCE_DIV_MEAN
static int	VARIANCE_DIV_MEAN_SQUARE

Fields inherited from interface ij.plugin.filter.PlugInFilter

CONVERT_TO_FLOAT, DOES_16, DOES_32, DOES_8C, DOES_8G, DOES_ALL, DOES_RGB, DOES_STACKS, DONE, FINAL_PROCESSING, KEEP_THRESHOLD, NO_CHANGES, NO_IMAGE_REQUIRED, NO_UNDO, NO_UNDO_RESET, PARALLELIZE_IMAGES, PARALLELIZE_STACKS, ROI_REQUIRED, SNAPSHOT, STACK_REQUIRED, SUPPORTS_MASKING

Constructor Summary

Constructors

Constructor and Description
Kuwahara()

Method Summary

Modifier and Type	Method and Description
boolean	applyFilter(ij.process.ImageProcessor inputImage, int size, int nAngles, int criterion) Apply filter to input image (in place)
void	calculateCriterionVariance(float[][] imSum, float[][] imSumOfSquares, float kernelSum, float[][] value, float[][] criterion)
void	calculateCriterionVarianceDivMean(float[][] imSum, float[][] imSumOfSquares, float kernelSum, float[][] value, float[][] criterion)
void	calculateCriterionVarianceDivMean2(float[][] imSum, float[][] imSumOfSquares, float kernelSum, float[][] value, float[][] criterion)
ij.ImageStack	createKernel(int size, int nAngles) create the convolution kernel
void	filter(ij.process.ImageProcessor ipData, ij.ImageStack imsKernels) Apply Kuwahara filter to input image
void	run(ij.process.ImageProcessor ipData) Run method for plugin filter
void	setCriterionMethod(int criterion) Set the criterion method
void	setNumberOfAngles(int nAngles)
void	setSize(int size)
int	setup(String arg, ij.ImagePlus imp)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

imW

protected int imW

imH

protected int imH

kW

protected int kW

kH

protected int kH

nAngles

protected int nAngles

size

protected int size

showKernels

protected boolean showKernels

VARIANCE

public static final int VARIANCE

See Also:

Constant Field Values

VARIANCE_DIV_MEAN

public static final int VARIANCE_DIV_MEAN

See Also:

Constant Field Values

VARIANCE_DIV_MEAN_SQUARE

public static final int VARIANCE_DIV_MEAN_SQUARE

See Also:

Constant Field Values

Constructor Detail

Kuwahara

public Kuwahara()

Method Detail

setup

public int setup(String arg,
                 ij.ImagePlus imp)

Specified by:

setup in interface ij.plugin.filter.PlugInFilter

run

public void run(ij.process.ImageProcessor ipData)

Run method for plugin filter

Specified by:

run in interface ij.plugin.filter.PlugInFilter

setCriterionMethod

public void setCriterionMethod(int criterion)

Set the criterion method

Parameters:

criterion -

setNumberOfAngles

public void setNumberOfAngles(int nAngles)

setSize

public void setSize(int size)

createKernel

public ij.ImageStack createKernel(int size,
                                  int nAngles)

create the convolution kernel

filter

public void filter(ij.process.ImageProcessor ipData,
                   ij.ImageStack imsKernels)

Apply Kuwahara filter to input image

Parameters:

ipData -

imsKernels -

calculateCriterionVariance

public final void calculateCriterionVariance(float[][] imSum,
                                             float[][] imSumOfSquares,
                                             float kernelSum,
                                             float[][] value,
                                             float[][] criterion)

calculateCriterionVarianceDivMean

public final void calculateCriterionVarianceDivMean(float[][] imSum,
                                                    float[][] imSumOfSquares,
                                                    float kernelSum,
                                                    float[][] value,
                                                    float[][] criterion)

calculateCriterionVarianceDivMean2

public final void calculateCriterionVarianceDivMean2(float[][] imSum,
                                                     float[][] imSumOfSquares,
                                                     float kernelSum,
                                                     float[][] value,
                                                     float[][] criterion)

applyFilter

public boolean applyFilter(ij.process.ImageProcessor inputImage,
                           int size,
                           int nAngles,
                           int criterion)

Apply filter to input image (in place)

Parameters:

inputImage - input image

size - kernel size (it must be odd)

nAngles - number of angles

Returns:

false if error