Package gov.nih.mipav.model.algorithms

Class AlgorithmSimulatedExposureFusion

java.lang.Object

java.lang.Thread

gov.nih.mipav.model.algorithms.AlgorithmBase

gov.nih.mipav.model.algorithms.AlgorithmSimulatedExposureFusion

All Implemented Interfaces:

ActionListener, WindowListener, Runnable, EventListener

public class AlgorithmSimulatedExposureFusion
extends AlgorithmBase

Nested Class Summary

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

Thread.Builder, Thread.State, Thread.UncaughtExceptionHandler

Field Summary

Fields

Modifier and Type	Field	Description
private double	a
private double	alpha	Original code from dispersionMap.m, multiscaleBlending.m, remapFun.m, robustNormalization.m, runsef.m, and sef.m located at https://github.com/chlsl/simulated-exposure-fusion-ipol was written by Charles Hessel and is being ported to Java with his permission.
private double	b
private double	beta
final int	BORDER_CONSTANT
final int	BORDER_DEFAULT
final int	BORDER_REFLECT
final int	BORDER_REFLECT_101
final int	BORDER_REPLICATE
final int	BORDER_WRAP
private double	epsilon
private double	lambda
private int	M
private double	med
private int	Mp
private int	N
private int	Ns
private int	nScales
private int	Nx

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
AlgorithmSimulatedExposureFusion()
AlgorithmSimulatedExposureFusion(ModelImage destImg, ModelImage srcImg, double alpha, double beta, int nScales, int M, double med, double lambda)

Method Summary

Modifier and Type	Method	Description
double[][]	copyMakeBorder(double[][] src, int top, int bottom, int left, int right, int borderType, double borderValue)
private double[]	dg(double[] t, int k)
private double[]	dh(double[] t, int k)
private double[]	dhs(double[] t, int k)
private double[][]	downsample(double[][] I, double[][] filter)
private double[]	f(double[] t, int k)
private double[][]	filter2Same(double[][] img, double[][] win)
private double[]	fs(double[] t, int k)
private double[]	g(double[] t, int k)
(package private) Vector<double[][]>	gaussian_pyramid(double[][] I, int nlev)
private double[]	h(double[] t, int k)
private double[]	hs(double[] t, int k)
(package private) Vector<double[][]>	laplacian_pyramid(double[][] I, int nlev)
private double[][]	multiscaleBlending(double[][][] seq, double[][][] W, int nScales)
private double[][]	pyramid_filter()
private double	r(int k)
private double[][]	reconstruct_laplacian_pyramid(Vector<double[][]> pyr)
void	runAlgorithm()	Actually runs the algorithm.
private double[][]	upsample(double[][] I, int[] odd, double[][] filter)

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

actionPerformed, addListener, addProgressChangeListener, calculateImageSize, calculatePrincipleAxis, computeElapsedTime, computeElapsedTime, convertIntoFloat, delinkProgressToAlgorithm, delinkProgressToAlgorithmMulti, displayError, errorCleanUp, finalize, 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, isVirtual, join, join, join, join, ofPlatform, ofVirtual, onSpinWait, resume, setContextClassLoader, setDaemon, setDefaultUncaughtExceptionHandler, setName, setPriority, setUncaughtExceptionHandler, sleep, sleep, sleep, start, startVirtualThread, stop, suspend, threadId, toString, yield

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Details

alpha

private double alpha

Original code from dispersionMap.m, multiscaleBlending.m, remapFun.m, robustNormalization.m, runsef.m, and sef.m located at https://github.com/chlsl/simulated-exposure-fusion-ipol was written by Charles Hessel and is being ported to Java with his permission. This method was first described in the following paper: HESSEL, Charles, MOREL, Jean-Michel, An Extended Exposure Fusion and its Application to Single Image Contrast Enhancement. In: 2020 IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE, 2020. For robustNormalization.m refer to: Charles Hessel, An Implementation of the Exposure Fusion Algorithm, Image Processing On Line, 8 (2018), pp. 369–387. https://doi.org/10.5201/ipol.2018.230 The code provided by Charles Hessel makes use of downsample.m, gaussian_pyramid.m, laplacian_pyramid.m, pyramid_filter.m, reconstruct_laplacian_pyramid.m, and upsample.m, which is from code located at https://github.com/Mericam/exposure-fusion that is covered under the BSD-2-Clause license: Copyright (c) 2015, Tom Mertens, tom.mertens@gmail.com All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Implementation of Exposure Fusion in Matlab, as described in: "Exposure Fusion", Tom Mertens, Jan Kautz and Frank Van Reeth In proceedings of Pacific Graphics 2007 "Exposure Fusion: A Simple and Practical Alternative to High Dynamic Range Photography. " Tom Mertens, Jan Kautz and Frank Van Reeth In Computer Graphics Forum, 28 (1) 161 - 171, 2009 This code was originally written by Tom Mertens at Hasselt University, August 2007. Uploaded to GitHub in February 2015 Author and main contact: Tom Mertens, tom.mertens@gmail.com

beta

private double beta

nScales

private int nScales

M

private int M

med

private double med

lambda

private double lambda

Nx

private int Nx

Mp

private int Mp

Ns

private int Ns

N

private int N

a

private double a

b

private double b

epsilon

private double epsilon

BORDER_CONSTANT

public final int BORDER_CONSTANT

See Also:

• Constant Field Values

BORDER_REPLICATE

public final int BORDER_REPLICATE

See Also:

• Constant Field Values

BORDER_REFLECT

public final int BORDER_REFLECT

See Also:

• Constant Field Values

BORDER_WRAP

public final int BORDER_WRAP

See Also:

• Constant Field Values

BORDER_REFLECT_101

public final int BORDER_REFLECT_101

See Also:

• Constant Field Values

BORDER_DEFAULT

public final int BORDER_DEFAULT

See Also:

• Constant Field Values

Constructor Details

AlgorithmSimulatedExposureFusion

public AlgorithmSimulatedExposureFusion()

AlgorithmSimulatedExposureFusion

public AlgorithmSimulatedExposureFusion(ModelImage destImg,
 ModelImage srcImg,
 double alpha,
 double beta,
 int nScales,
 int M,
 double med,
 double lambda)

Method Details

runAlgorithm

public void runAlgorithm()

Description copied from class: AlgorithmBase

Actually runs the algorithm. Implemented by inheriting algorithms.

Specified by:

runAlgorithm in class AlgorithmBase

multiscaleBlending

private double[][] multiscaleBlending(double[][][] seq,
 double[][][] W,
 int nScales)

reconstruct_laplacian_pyramid

private double[][] reconstruct_laplacian_pyramid(Vector<double[][]> pyr)

laplacian_pyramid

Vector<double[][]> laplacian_pyramid(double[][] I,
 int nlev)

upsample

private double[][] upsample(double[][] I,
 int[] odd,
 double[][] filter)

gaussian_pyramid

Vector<double[][]> gaussian_pyramid(double[][] I,
 int nlev)

downsample

private double[][] downsample(double[][] I,
 double[][] filter)

copyMakeBorder

public double[][] copyMakeBorder(double[][] src,
 int top,
 int bottom,
 int left,
 int right,
 int borderType,
 double borderValue)

filter2Same

private double[][] filter2Same(double[][] img,
 double[][] win)

pyramid_filter

private double[][] pyramid_filter()

f

private double[] f(double[] t,
 int k)

fs

private double[] fs(double[] t,
 int k)

r

private double r(int k)

g

private double[] g(double[] t,
 int k)

h

private double[] h(double[] t,
 int k)

hs

private double[] hs(double[] t,
 int k)

dg

private double[] dg(double[] t,
 int k)

dh

private double[] dh(double[] t,
 int k)

dhs

private double[] dhs(double[] t,
 int k)