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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) 2023, 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.block;

import boofcv.struct.image.*;

/**
 * Computes the Sum of Absolute Difference (SAD) for block matching based algorithms.
 *
 * 
 * Notes on scoreSad():

 * compute the score for each element all at once to encourage the JVM to optimize and
 * encourage the JVM to optimize this section of code.
 * 
 *
 * 
 * Was original inline, but was actually slightly slower by about 3% consistently,  It
 * is in its own function so that it can be overridden and have different cost functions
 * inserted easily.
 * 
 *
 * @author Peter Abeles
 */
public interface BlockRowScoreSad {
	abstract class SadArrayS32, ImageData> extends BlockRowScore.ArrayS32_BS32 {
		SadArrayS32( int maxPerPixel ) {
			super(maxPerPixel);
		}

		@Override
		public boolean isRequireNormalize() {
			return false;
		}
	}

	abstract class SadArrayF32 extends BlockRowScore.ArrayS32_BF32 {
		@Override
		public boolean isRequireNormalize() {
			return false;
		}

		@Override
		public int getMaxPerPixelError() {
			throw new RuntimeException("Not supported for float images");
		}
	}

	class U8 extends SadArrayS32 {
		public U8() {
			super(255);
		}

		@Override
		public void score( byte[] leftRow, byte[] rightRow, int indexLeft, int indexRight, int offset, int length, int[] elementScore ) {
			for (int i = 0; i < length; i++) {
				int difference = (leftRow[indexLeft++] & 0xFF) - (rightRow[indexRight++] & 0xFF);
				elementScore[offset + i] = Math.abs(difference);
			}
		}

		@Override
		public ImageType getImageType() {
			return ImageType.SB_U8;
		}
	}

	class U16 extends SadArrayS32 {
		public U16() {
			super(-1);
		}

		@Override
		public void score( short[] leftRow, short[] rightRow, int indexLeft, int indexRight, int offset, int length, int[] elementScore ) {
			for (int i = 0; i < length; i++) {
				int difference = (leftRow[indexLeft++] & 0xFFFF) - (rightRow[indexRight++] & 0xFFFF);
				elementScore[offset + i] = Math.abs(difference);
			}
		}

		@Override
		public ImageType getImageType() {
			return ImageType.SB_U16;
		}
	}

	class S16 extends SadArrayS32 {
		public S16() {
			super(-1);
		}

		@Override
		public void score( short[] leftRow, short[] rightRow, int indexLeft, int indexRight, int offset, int length, int[] elementScore ) {
			for (int rCol = 0; rCol < length; rCol++) {
				int difference = leftRow[indexLeft++] - rightRow[indexRight++];
				elementScore[offset + rCol] = Math.abs(difference);
			}
		}

		@Override
		public ImageType getImageType() {
			return ImageType.SB_S16;
		}
	}

	class F32 extends SadArrayF32 {
		@Override
		public void score( float[] leftRow, float[] rightRow, int indexLeft, int indexRight, int offset, int length, float[] elementScore ) {
			for (int i = 0; i < length; i++) {
				float difference = leftRow[indexLeft++] - rightRow[indexRight++];
				elementScore[offset + i] = Math.abs(difference);
			}
		}

		@Override
		public ImageType getImageType() {
			return ImageType.SB_F32;
		}
	}
}