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ISTA.java
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ISTA.java
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/*
* DeconvolutionLab2
*
* Conditions of use: You are free to use this software for research or
* educational purposes. In addition, we expect you to include adequate
* citations and acknowledgments whenever you present or publish results that
* are based on it.
*
* Reference: DeconvolutionLab2: An Open-Source Software for Deconvolution
* Microscopy D. Sage, L. Donati, F. Soulez, D. Fortun, G. Schmit, A. Seitz,
* R. Guiet, C. Vonesch, M Unser, Methods of Elsevier, 2017.
*/
/*
* Copyright 2010-2017 Biomedical Imaging Group at the EPFL.
*
* This file is part of DeconvolutionLab2 (DL2).
*
* DL2 is free software: you can redistribute it and/or modify it under the
* terms of the GNU General Public License as published by the Free Software
* Foundation, either version 3 of the License, or (at your option) any later
* version.
*
* DL2 is distributed in the hope that it will be useful, but WITHOUT ANY
* WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
* A PARTICULAR PURPOSE. See the GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License along with
* DL2. If not, see <http://www.gnu.org/licenses/>.
*/
package deconvolution.algorithm;
import java.util.concurrent.Callable;
import signal.ComplexSignal;
import signal.Operations;
import signal.RealSignal;
import wavelets.AbstractWavelets;
import wavelets.Wavelets;
public class ISTA extends AbstractAlgorithm implements Callable<RealSignal> {
private double gamma = 1.0;
private double lambda = 1.0;
private String waveletsName = "Haar";
private int scale = 3;
public ISTA(int iter, double gamma, double lambda, String waveletsName, int scale) {
super();
controller.setIterationMax(iter);
this.gamma = gamma;
this.lambda = lambda;
this.waveletsName = waveletsName;
this.scale = scale;
}
@Override
public RealSignal call() throws Exception {
AbstractWavelets wavelets = Wavelets.getWaveletsByName(waveletsName);
wavelets.setScale(scale);
ComplexSignal Y = fft.transform(y);
ComplexSignal H = fft.transform(h);
ComplexSignal A = Operations.delta(gamma, H);
ComplexSignal G = Operations.multiplyConjugate(gamma, H, Y);
ComplexSignal Z = G.duplicate();
RealSignal x = fft.inverse(G);
RealSignal z = x.duplicate();
float threshold = (float)(lambda*gamma*0.5);
RealSignal buffer = y.duplicate();
while(!controller.ends(x)) {
fft.transform(x, Z);
Z.times(A);
Z.plus(G);
fft.inverse(Z, z);
wavelets.shrinkage(threshold, z, x, buffer);
}
return x;
}
public void update(RealSignal xprev, RealSignal x, double w, RealSignal s) {
int nxy = x.nx * x.ny;
for(int k=0; k<x.nz; k++)
for(int i=0; i< nxy; i++) {
float vx = x.data[k][i];
s.data[k][i] = (float)(vx + w*(vx - xprev.data[k][i]));
xprev.data[k][i] = vx;
}
}
@Override
public String getName() {
return "ISTA";
}
@Override
public String getShortname() {
return "ISTA";
}
@Override
public boolean isRegularized() {
return true;
}
@Override
public boolean isStepControllable() {
return true;
}
@Override
public boolean isIterative() {
return true;
}
@Override
public boolean isWaveletsBased() {
return true;
}
@Override
public void setWavelets(String waveletsName) {
this.waveletsName = waveletsName;
}
@Override
public void setParameters(double[] params) {
if (params == null)
return;
if (params.length > 0)
controller.setIterationMax((int)Math.round(params[0]));
if (params.length > 1)
gamma = (float)params[1];
if (params.length > 2)
lambda = (float)params[2];
if (params.length > 3)
scale = (int)params[3];
}
@Override
public double[] getDefaultParameters() {
return new double[] {10, 1, 0.1};
}
@Override
public double[] getParameters() {
return new double[] {controller.getIterationMax(), gamma, lambda};
}
@Override
public double getRegularizationFactor() {
return lambda;
}
@Override
public double getStepFactor() {
return gamma;
}
}

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