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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.struct.image.GrayU16;
import boofcv.struct.image.ImageBase;
import boofcv.struct.image.Planar;

/**
 * Computes a stack of matching costs for all pixels across all possible disparities for use
 * with {@link SgmCostAggregation}. Pay close attention to the element ordering in the output. Ordering was
 * selected to reduce CPU cache misses when aggregating the costs.
 *
 * The output is really a 3D tensor, but to avoid creating another custom data type planar images are used.
 * The other reason to use a planar image is that it was desirable to have multiple arrays define the tensor.
 *
 * 
 * Format of costYXD. YXD indicates the ordering of values in the tensor. The outer most is T, which is the bands.
 * X is the row in a planar image and D the columns. Thus, (y,x,d) = costYXD.getBand(y).get(d,x-disparityMin).
 * 
 *
 * @author Peter Abeles
 */
public interface SgmDisparityCost> {

	/**
	 * Maximum allowed cost fo a disparity 11-bits as suggested in the paper
	 */
	int MAX_COST = 2048 - 1;

	/**
	 * Configures the disparity search
	 *
	 * @param disparityMin Minimum possible disparity, inclusive
	 * @param disparityRange Number of possible disparity values estimated. The max possible disparity is min+range-1.
	 */
	void configure( int disparityMin, int disparityRange );

	/**
	 * Computes the score for all possible disparity values across all pixels. If a disparity value would
	 * go outside of the image then the cost is set to {@link #MAX_COST}
	 *
	 * @param left left image
	 * @param right right image
	 * @param costYXD Cost of output scaled to have a range of 0 to {@link SgmDisparityCost#MAX_COST}, inclusive.
	 * Reshaped to match input and disparity range.
	 */
	void process( T left, T right, Planar costYXD );
}