/*
* Gray8WienerDeconv.java
*
* Created on November 3, 2007, 3:07 PM
*
* To change this template, choose Tools | Template Manager
* and open the template in the editor.
*
* Copyright 2007 by Jon A. Webb
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program 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 Lesser General Public License for more details.
*
* You should have received a copy of the Lesser GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*
*/
package jjil.algorithm;
import jjil.core.Complex;
import jjil.core.Complex32Image;
import jjil.core.Error;
import jjil.core.Gray32Image;
import jjil.core.Gray8Image;
import jjil.core.Image;
import jjil.core.MathPlus;
import jjil.core.PipelineStage;
/**
* Wiener deconvolution of input Gray8Image. You specify a point spread function
* as a Gray8Image and a noise level. See PsfGray8 for point spread function
* generating methods. The computation is done in the Fourier domain. The output
* is of type Complex32Image.
* @author webb
*/
public class Gray8WienerDeconv extends PipelineStage {
private int nNoise;
private static final int nThreshold = 5;
Gray8Fft fft;
Complex32Image cxmPsfInv;
Gray32Image gPsfSq;
/**
* Creates a new instance of Gray8WienerDeconv.
* @param psf the input point spread function. This is the expected blur
* window, for example a disk or rectangle.
* @param nNoise the noise level.
* @throws jjil.core.Error if the input point spread function is not a Gray8Image or not square.
*/
public Gray8WienerDeconv(Gray8Image psf, int nNoise) throws jjil.core.Error {
if (psf.getWidth() != psf.getHeight()) {
throw new Error(
Error.PACKAGE.ALGORITHM,
ErrorCodes.IMAGE_NOT_SQUARE,
psf.toString(),
null,
null);
}
if (!(psf instanceof Gray8Image)) {
throw new Error(
Error.PACKAGE.ALGORITHM,
ErrorCodes.IMAGE_NOT_GRAY8IMAGE,
psf.toString(),
null,
null);
}
this.nNoise = nNoise;
this.fft = new Gray8Fft();
this.fft.push(psf);
this.cxmPsfInv = (Complex32Image) this.fft.getFront();
invertPsf();
}
/**
* Compute the deconvolution of the input Gray8Image, producing a Complex32Image.
* @param im the input Gray8Image.
* @throws jjil.core.Error if the input image is not a Gray8Image or not square.
*/
public void push(Image im) throws jjil.core.Error {
if (im.getWidth() != im.getHeight()) {
throw new Error(
Error.PACKAGE.ALGORITHM,
ErrorCodes.IMAGE_NOT_SQUARE,
im.toString(),
null,
null);
}
if (im.getWidth() != this.cxmPsfInv.getWidth() ||
im.getHeight() != this.cxmPsfInv.getHeight()) {
throw new Error(
Error.PACKAGE.ALGORITHM,
ErrorCodes.IMAGE_SIZES_DIFFER,
im.toString(),
this.cxmPsfInv.toString(),
null);
}
if (!(im instanceof Gray8Image)) {
throw new Error(
Error.PACKAGE.ALGORITHM,
ErrorCodes.IMAGE_NOT_GRAY8IMAGE,
im.toString(),
null,
null);
}
this.fft.push(im);
Complex32Image cxmIm = (Complex32Image) this.fft.getFront();
Complex cxIn[] = cxmIm.getData();
Complex32Image cxmResult = new Complex32Image(im.getWidth(), im.getHeight());
Complex cxOut[] = cxmResult.getData();
Complex cxPsfInv[] = this.cxmPsfInv.getData();
int nPsfSq[] = this.gPsfSq.getData();
// compute Wiener filter
for (int i=0; i<im.getWidth() * im.getHeight(); i++) {
int nMag = cxIn[i].magnitude();
int nScale = (nPsfSq[i] * nMag) / ((nPsfSq[i] * nMag) + this.nNoise);
cxOut[i] = cxIn[i].times(cxPsfInv[i]).times(nScale).rsh(MathPlus.SHIFT);
}
super.setOutput(cxmResult);
}
private void invertPsf() throws jjil.core.Error {
this.gPsfSq = new Gray32Image(this.cxmPsfInv.getWidth(), this.cxmPsfInv.getHeight());
Complex cxPsf[] = this.cxmPsfInv.getData();
int nData[] = this.gPsfSq.getData();
for (int i=0; i<this.cxmPsfInv.getWidth() * this.cxmPsfInv.getHeight(); i++) {
if (Math.abs(cxPsf[i].real()) > MathPlus.SCALE ||
Math.abs(cxPsf[i].imag()) > MathPlus.SCALE) {
cxPsf[i] = new Complex(0);
nData[i] = 1;
} else {
int nSq = cxPsf[i].square();
nData[i] = nSq;
if (nSq < Gray8WienerDeconv.nThreshold) {
// if the square value is too small we will be enhancing noise
// too much
cxPsf[i] = new Complex(MathPlus.SCALE);
nData[i] = 1;
} else {
cxPsf[i] = new Complex(MathPlus.SCALE).div(cxPsf[i]);
}
}
}
}
}