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/*
* 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.alg.misc;
import boofcv.struct.image.ImageGray;
import org.jetbrains.annotations.Nullable;
/**
* Functions related to adjusting input pixels to ensure they have a known and fixed range. Can handle the
* conversion of integer to float images. Output is always float.
*
* @author Peter Abeles
*/
public class ImageNormalization {
/**
* Applies the normalization to the image.
*
* @param input Input image.
* @param parameter Normalziation parameters
* @param output Output image. Can be the same instance as the input image.
*/
public static void apply( ImageGray input, NormalizeParameters parameter, ImageGray output ) {
GPixelMath.plus(input, parameter.offset, output);
GPixelMath.multiply(output, 1.0f/parameter.divisor, output);
}
/**
* Normalizes the image so that the max abs of the image is 1.
*
* @param input Input image
* @param output Scaled output image.
* @param parameters the parameters
*/
public static void maxAbsOfOne( ImageGray input, ImageGray output, @Nullable NormalizeParameters parameters ) {
output.reshape(input);
if (output.getDataType().isInteger())
throw new IllegalArgumentException("Output must be a floating point image");
double scale = GImageStatistics.maxAbs(input);
if (scale == 0.0) {
scale = 1.0;
} else {
GPixelMath.multiply(input, 1.0f/scale, output);
}
if (parameters != null) {
parameters.offset = 0.0;
parameters.divisor = scale;
}
}
/**
* Ensures that the output image has a mean zero and a max abs(pixel) of 1
*
* @param input Input image
* @param output Scaled output image.
*/
public static void zeroMeanMaxOne( ImageGray input, ImageGray output, @Nullable NormalizeParameters parameters ) {
output.reshape(input);
if (output.getDataType().isInteger())
throw new IllegalArgumentException("Output must be a floating point image");
// Numerical errors is a concern and if you sum up the input it could overflow
double scale = GImageStatistics.maxAbs(input);
if (scale != 0.0) {
GPixelMath.multiply(input, 1.0f/scale, output);
// Work with this scaled image
double mean = GImageStatistics.mean(output);
GPixelMath.minus(output, mean, output);
double scale2;
if (input.getDataType().isSigned()) {
scale2 = GImageStatistics.maxAbs(output);
} else {
// image is scaled from 0 to 1.0
scale2 = mean < 0.5 ? 1.0 - mean : mean;
}
if (scale2 != 0.0)
GPixelMath.multiply(output, 1.0f/scale2, output);
else
scale2 = 1.0;
if (parameters != null) {
parameters.offset = -mean*scale;
parameters.divisor = scale*scale2;
}
} else {
if (parameters != null) {
parameters.offset = 0.0;
parameters.divisor = 1.0;
}
}
}
/**
* Ensures that the output image has a mean zero and a standard deviation of 1. This is often the recommended
* approach.
*
* @param input Input image
* @param output Scaled output image.
*/
public static void zeroMeanStdOne( ImageGray input, ImageGray output, @Nullable NormalizeParameters parameters ) {
output.reshape(input);
if (output.getDataType().isInteger())
throw new IllegalArgumentException("Output must be a floating point image");
// avoid overflow
double scale = GImageStatistics.maxAbs(input);
if (scale != 0.0) {
GPixelMath.multiply(input, 1.0f/scale, output);
double mean = GImageStatistics.mean(output);
double stdev = Math.sqrt(GImageStatistics.variance(output, mean));
GPixelMath.minus(output, mean, output);
if (stdev != 0.0) {
GPixelMath.multiply(output, 1.0f/stdev, output);
} else {
stdev = 1.0;
}
if (parameters != null) {
parameters.offset = -mean*scale;
parameters.divisor = stdev*scale;
}
} else {
if (parameters != null) {
parameters.offset = 0.0;
parameters.divisor = 1.0;
}
}
}
}
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