boofcv.alg.denoise.wavelet.DenoiseSureShrink_F32 Maven / Gradle / Ivy

Go to download

Show more of this group Show more artifacts with this name
Show all versions of ip Show documentation

BoofCV is an open source Java library for real-time computer vision and robotics applications.

There is a newer version: 0.26

/*
 * 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 java.util.Arrays;


/**
 * 
 * SureShrink denoises wavelets using a threshold computed by minimizing Stein's Unbiased Risk
 * Estimate (SURE).  In practice a hybrid approach was found to work best where either the Stein
 * threshold or the universal threshold proposed by VisuShrink is used.
 * 
 *
 * 
 * This implementation computes a threshold for each subband.
 * 
 *
 * 
 * D. Donoho, L. Johnstone, "Adapting to Unknown Smoothness via Wavelet Shrinkage"
 * Journal of the American Statistical Association, Vol. 90, No. 432, December 1995, pp. 1200-1224
 * 
 *
 * @author Peter Abeles
 */
public class DenoiseSureShrink_F32 extends SubbandShrink {

	float noiseSigma;

	public DenoiseSureShrink_F32() {
		super(new ShrinkThresholdSoft_F32());
	}

	@Override
	protected Number computeThreshold( GrayF32 subband  )
	{
		float coef[] = new float[ subband.width*subband.height ];
		UtilDenoiseWavelet.subbandAbsVal(subband,coef);
		Arrays.sort(coef);

		float maxThreshold =(float) UtilDenoiseWavelet.universalThreshold(subband,1.0);

		float N = coef.length;

		float threshold = maxThreshold;
		float bestRisk = Float.MAX_VALUE;
		float sumW = 0;
		float right = N-2.0f;
		for( int i = 0; i < coef.length; i++ , right -= 2.0f) {
			float c = coef[i]/noiseSigma;
			if( c > maxThreshold ) {
				break;
			}

			float cc = c*c;
			sumW += cc;
			float risk = sumW + cc*(N-i-1.0f) + right;
			if( risk < bestRisk ) {
				threshold = c;
				bestRisk = risk;
			}
		}

		return noiseSigma*threshold;
	}

	@Override
	public void denoise(GrayF32 transform , int numLevels ) {

		int w = transform.width;
		int h = transform.height;

		// compute the noise variance using the HH_1 subband
		noiseSigma = UtilDenoiseWavelet.estimateNoiseStdDev(transform.subimage(w/2,h/2,w,h, null),null);

//		System.out.println("Noise sigma: "+noiseSigma);

		performShrinkage(transform,numLevels);
	}
}