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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) 2021, 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.factory.disparity;

import boofcv.factory.transform.census.CensusVariants;
import boofcv.struct.Configuration;
import boofcv.struct.pyramid.ConfigDiscreteLevels;

/**
 * Configurations for different types of disparity error metrics
 *
 * @author Peter Abeles
 */
public interface ConfigDisparityError extends Configuration {
	/**
	 * Configuration for Census
	 */
	class Census implements ConfigDisparityError {
		public CensusVariants variant = CensusVariants.BLOCK_5_5;

		@Override
		public void checkValidity() {}

		public Census setTo( Census src ) {
			this.variant = src.variant;
			return this;
		}
	}

	/**
	 * Normalized cross correlation error
	 */
	class NCC implements ConfigDisparityError {

		/**
		 * Used to avoid a divide by zero error when dividing by the standard deviation. Only used with NCC. Smaller
		 * values are more mathematically accurate but make it more sensitive to floating point error.
		 * This has been tuned to work with pixel values that have been scaled to -1 to 1.
		 */
		public double eps = 5.5e-6;

		/**
		 * If true then the input will be normalized so that it has zero mean and a max absolute value of one. Reduces
		 * numerical issues.
		 */
		public boolean normalizeInput = true;

		@Override public void checkValidity() {}

		public NCC setTo( NCC src ) {
			this.eps = src.eps;
			this.normalizeInput = src.normalizeInput;
			return this;
		}
	}

	/**
	 * Configuration for Hierarchical Mutual Information.
	 */
	class HMI implements ConfigDisparityError {
		/**
		 * Number of possible pixel values. MI was designed around 8-bit images and performance will
		 * degrade for large values.
		 */
		public int totalGrayLevels = 256;
		/**
		 * Specifies the smallest layer in pyramid. Used to compute Mutual Information Cost
		 */
		public ConfigDiscreteLevels pyramidLayers = new ConfigDiscreteLevels(-1, 50, -1);
		/**
		 * Radius of Gaussian kernel when applying smoothing during Mutual Information computation.
		 */
		public int smoothingRadius = 3;

		/**
		 * Number of additional iterations to perform. This should improve the MI estimate, but the cost
		 * is significant.
		 */
		public int extraIterations = 0;

		@Override public void checkValidity() {}

		public HMI setTo( HMI src ) {
			this.totalGrayLevels = src.totalGrayLevels;
			this.pyramidLayers.setTo(src.pyramidLayers);
			this.smoothingRadius = src.smoothingRadius;
			this.extraIterations = src.extraIterations;
			return this;
		}
	}
}