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

There is a newer version: 1.1.7

/*
 * Copyright (c) 2022, 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.disparity.sgm;

import boofcv.abst.filter.FilterImageInterface;
import boofcv.alg.InputSanityCheck;
import boofcv.struct.image.ImageBase;
import boofcv.struct.image.ImageGray;

/**
 * Computes Census score for SGM using a straight forward implementation. A census transform is applied
 * to the left and right input images. That's then used to compute the census error.
 *
 * @author Peter Abeles
 */
public class SgmStereoDisparityCensus, C extends ImageGray>
		extends SgmStereoDisparity {
	FilterImageInterface censusTran;
	// Storage for census transform of left and right images
	C cleft;
	C cright;

	public SgmStereoDisparityCensus( FilterImageInterface censusTran,
									 SgmDisparityCost sgmCost, SgmDisparitySelector selector ) {
		super(sgmCost, selector);

		this.censusTran = censusTran;
		cleft = censusTran.getOutputType().createImage(1, 1);
		cright = censusTran.getOutputType().createImage(1, 1);
	}

	/**
	 * Computes disparity
	 *
	 * @param left (Input) left rectified stereo image
	 * @param right (Input) right rectified stereo image
	 */
	@Override
	public void process( T left, T right ) {
		InputSanityCheck.checkSameShape(left, right);

		// Apply Census Transform to input images
		censusTran.process(left, cleft);
		censusTran.process(right, cright);

		disparity.reshape(left);
		helper.configure(left.width, disparityMin, disparityRange);
		sgmCost.configure(disparityMin, disparityRange);
		aggregation.configure(disparityMin);

		// Compute the cost using mutual information
		sgmCost.process(cleft, cright, costYXD);
		// Aggregate the cost along all the paths
		aggregation.process(costYXD);

		// Select the best disparity for each pixel given the cost
		selector.setDisparityMin(disparityMin);
		selector.select(costYXD, aggregation.getAggregated(), disparity);
	}
}