/*
* Copyright (c) 2011-2016, Peter Abeles. All Rights Reserved.
*
* This file is part of BoofCV (http://boofcv.org).
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package boofcv.alg.denoise.wavelet;
import boofcv.struct.image.GrayF32;
import boofcv.struct.image.ImageGray;
import org.ddogleg.sorting.QuickSelect;
/**
* Various functions useful for denoising wavelet transforms.
*
* @author Peter Abeles
*/
public class UtilDenoiseWavelet {
/**
* <p>
* Robust median estimator of the noise standard deviation. Typically applied to the HH<sub>1</sub> subband.
* </p>
*
* <p>
* σ = Median(|Y<sub>ij</sub>|)/0.6745<br>
* where σ is the estimated noise standard deviation, and Median(|Y<sub>ij</sub>|)
* is the median absolute value of all the pixels in the subband.
* </p>
*
* <p>
* D. L. Donoho and I. M. Johnstone, "Ideal spatial adaption via wavelet shrinkage."
* Biometrika, vol 81, pp. 425-455, 1994
* </p>
*
* @param subband The subband the image is being computed from. Not modified.
* @param storage Used to temporarily store the absolute value of each element in the subband.
* @return estimated noise variance.
*/
public static float estimateNoiseStdDev(GrayF32 subband , float storage[] ) {
storage = subbandAbsVal(subband, storage );
int N = subband.width*subband.height;
return QuickSelect.select(storage, N / 2, N)/0.6745f;
}
/**
* Computes the absolute value of each element in the subband image are places it into
* 'coef'
*/
public static float[] subbandAbsVal(GrayF32 subband, float[] coef ) {
if( coef == null ) {
coef = new float[subband.width*subband.height];
}
int i = 0;
for( int y = 0; y < subband.height; y++ ) {
int index = subband.startIndex + subband.stride*y;
int end = index + subband.width;
for( ;index < end; index++ ) {
coef[i++] = Math.abs(subband.data[index]);
}
}
return coef;
}
/**
* <p>
* Computes the universal threshold defined in [1], which is the threshold used by
* VisuShrink. The same threshold is used by other algorithms.
* </p>
*
* <p>
* threshold = σ sqrt( 2*log(max(w,h))<br>
* where (w,h) is the image's width and height.
* </p>
*
* <p>
* [1] D. L. Donoho and I. M. Johnstone, "Ideal spatial adaption via wavelet shrinkage."
* Biometrika, vol 81, pp. 425-455, 1994
* </p>
* @param image Input image. Only the width and height are used in computing this thresold.
* @param noiseSigma Estimated noise sigma.
* @return universal threshold.
*/
public static double universalThreshold(ImageGray image , double noiseSigma ) {
int w = image.width;
int h = image.height;
return noiseSigma*Math.sqrt(2*Math.log(Math.max(w,h)));
}
}