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BoofCV is an open source Java library for real-time computer vision and robotics applications.
/*
* Copyright (c) 2011-2017, 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.alg.InputSanityCheck;
import boofcv.struct.image.*;
import javax.annotation.Generated;
/**
* Computes statistical properties of pixels inside an image.
*
* DO NOT MODIFY: Generated by boofcv.alg.misc.GenerateImageStatistics
.
*
* @author Peter Abeles
*/
@Generated("boofcv.alg.misc.GenerateImageStatistics")
public class ImageStatistics {
/**
* Returns the minimum element value.
*
* @param input Input image. Not modified.
* @return Minimum pixel value.
*/
public static int min( GrayU8 input ) {
return minU( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the minimum element value.
*
* @param input Input image. Not modified.
* @return Minimum pixel value.
*/
public static int min( InterleavedU8 input ) {
return minU( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static int minU( byte[] array , int startIndex , int rows , int columns , int stride ) {
int output = array[startIndex]& 0xFF;
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
int v = array[index] & 0xFF;
if( v < output )
output = v;
}
}
return output;
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static int max( GrayU8 input ) {
return maxU( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static int max( InterleavedU8 input ) {
return maxU( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static int maxU( byte[] array , int startIndex , int rows , int columns , int stride ) {
int output = array[startIndex]& 0xFF;
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
int v = array[index] & 0xFF;
if( v > output )
output = v;
}
}
return output;
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static int maxAbs( GrayU8 input ) {
return maxAbsU( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static int maxAbs( InterleavedU8 input ) {
return maxAbsU( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static int maxAbsU( byte[] array , int startIndex , int rows , int columns , int stride ) {
int output = array[startIndex]& 0xFF;
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
int v = array[index] & 0xFF;
if( v > output )
output = v;
}
}
return output;
}
/**
* Computes the mean squared error (MSE) between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffSq(GrayU8 imgA, GrayU8 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffSqU(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width);
}
/**
* Computes the mean squared error (MSE) between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffSq(InterleavedU8 imgA, InterleavedU8 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffSqU(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width*imgA.numBands);
}
private static double meanDiffSqU(byte []dataA, int startIndexA , int strideA,
byte []dataB, int startIndexB , int strideB,
int rows , int columns ) {
int total = 0;
for (int y = 0; y < rows; y++) {
int indexA = startIndexA + y * strideA;
int indexB = startIndexB + y * strideB;
int indexEnd = indexA+columns;
for (; indexA < indexEnd; indexA++,indexB++) {
int difference = (dataA[indexA]& 0xFF)-(dataB[indexB]& 0xFF);
total += difference*difference;
}
}
return total / (double)(rows*columns);
}
/**
* Computes the mean of absolute value error between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffAbs(GrayU8 imgA, GrayU8 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffAbsU(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width);
}
/**
* Computes the mean of absolute value error between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffAbs(InterleavedU8 imgA, InterleavedU8 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffAbsU(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width*imgA.numBands);
}
private static double meanDiffAbsU(byte []dataA, int startIndexA , int strideA,
byte []dataB, int startIndexB , int strideB,
int rows , int columns ) {
int total = 0;
for (int y = 0; y < rows; y++) {
int indexA = startIndexA + y * strideA;
int indexB = startIndexB + y * strideB;
int indexEnd = indexA+columns;
for (; indexA < indexEnd; indexA++,indexB++) {
int difference = (dataA[indexA]& 0xFF)-(dataB[indexB]& 0xFF);
total += Math.abs(difference);
}
}
return total / (double)(rows*columns);
}
/**
*
* Returns the sum of all the pixels in the image.
*
*
* @param img Input image. Not modified.
*/
public static int sum( GrayU8 img ) {
final int rows = img.height;
final int columns = img.width;
int total = 0;
for (int y = 0; y < rows; y++) {
int index = img.startIndex + y * img.stride;
int indexEnd = index+columns;
for (; index < indexEnd; index++ ) {
total += img.data[index] & 0xFF;
}
}
return total;
}
/**
* Returns the mean pixel intensity value.
*
* @param img Input image. Not modified.
* @return Mean pixel intensity value
*/
public static double mean( GrayU8 img ) {
return sum(img)/(double)(img.width*img.height);
}
/**
*
* Returns the sum of all the pixels in the image.
*
*
* @param img Input image. Not modified.
*/
public static int sum( InterleavedU8 img ) {
final int rows = img.height;
final int columns = img.width*img.numBands;
int total = 0;
for (int y = 0; y < rows; y++) {
int index = img.startIndex + y * img.stride;
int indexEnd = index+columns;
for (; index < indexEnd; index++ ) {
total += img.data[index] & 0xFF;
}
}
return total;
}
/**
* Returns the mean pixel intensity value.
*
* @param img Input image. Not modified.
* @return Mean pixel intensity value
*/
public static double mean( InterleavedU8 img ) {
return sum(img)/(double)(img.width*img.height*img.numBands);
}
/**
* Computes the variance of pixel intensity values inside the image.
*
* @param img Input image. Not modified.
* @param mean Mean pixel intensity value.
* @return Pixel variance
*/
public static double variance( GrayU8 img , double mean ) {
double variance = 0;
for (int y = 0; y < img.height; y++) {
int index = img.getStartIndex() + y * img.getStride();
int indexEnd = index+img.width;
// for(int x = 0; x < img.width; x++ ) {
for (; index < indexEnd; index++ ) {
double d = (img.data[index]& 0xFF) - mean;
variance += d*d;
}
}
return variance/(img.width*img.height);
}
/**
* Computes the histogram of intensity values for the image.
*
* @param input (input) Image.
* @param minValue (input) Minimum possible intensity value
* @param histogram (output) Storage for histogram. Number of elements must be equal to max value.
*/
public static void histogram( GrayU8 input , int minValue , int histogram[] ) {
for( int i = 0; i < histogram.length; i++ )
histogram[i] = 0;
for( int y = 0; y < input.height; y++ ) {
int index = input.startIndex + y*input.stride;
int end = index + input.width;
for( ; index < end; index++ ) {
histogram[(input.data[index]& 0xFF) - minValue ]++;
}
}
}
/**
* Returns the minimum element value.
*
* @param input Input image. Not modified.
* @return Minimum pixel value.
*/
public static int min( GrayS8 input ) {
return min( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the minimum element value.
*
* @param input Input image. Not modified.
* @return Minimum pixel value.
*/
public static int min( InterleavedS8 input ) {
return min( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static int min( byte[] array , int startIndex , int rows , int columns , int stride ) {
int output = array[startIndex];
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
int v = array[index] ;
if( v < output )
output = v;
}
}
return output;
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static int max( GrayS8 input ) {
return max( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static int max( InterleavedS8 input ) {
return max( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static int max( byte[] array , int startIndex , int rows , int columns , int stride ) {
int output = array[startIndex];
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
int v = array[index] ;
if( v > output )
output = v;
}
}
return output;
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static int maxAbs( GrayS8 input ) {
return maxAbs( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static int maxAbs( InterleavedS8 input ) {
return maxAbs( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static int maxAbs( byte[] array , int startIndex , int rows , int columns , int stride ) {
int output = array[startIndex];
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
int v = Math.abs(array[index]);
if( v > output )
output = v;
}
}
return output;
}
/**
* Computes the mean squared error (MSE) between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffSq(GrayS8 imgA, GrayS8 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffSq(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width);
}
/**
* Computes the mean squared error (MSE) between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffSq(InterleavedS8 imgA, InterleavedS8 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffSq(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width*imgA.numBands);
}
private static double meanDiffSq(byte []dataA, int startIndexA , int strideA,
byte []dataB, int startIndexB , int strideB,
int rows , int columns ) {
int total = 0;
for (int y = 0; y < rows; y++) {
int indexA = startIndexA + y * strideA;
int indexB = startIndexB + y * strideB;
int indexEnd = indexA+columns;
for (; indexA < indexEnd; indexA++,indexB++) {
int difference = (dataA[indexA])-(dataB[indexB]);
total += difference*difference;
}
}
return total / (double)(rows*columns);
}
/**
* Computes the mean of absolute value error between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffAbs(GrayS8 imgA, GrayS8 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffAbs(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width);
}
/**
* Computes the mean of absolute value error between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffAbs(InterleavedS8 imgA, InterleavedS8 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffAbs(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width*imgA.numBands);
}
private static double meanDiffAbs(byte []dataA, int startIndexA , int strideA,
byte []dataB, int startIndexB , int strideB,
int rows , int columns ) {
int total = 0;
for (int y = 0; y < rows; y++) {
int indexA = startIndexA + y * strideA;
int indexB = startIndexB + y * strideB;
int indexEnd = indexA+columns;
for (; indexA < indexEnd; indexA++,indexB++) {
int difference = (dataA[indexA])-(dataB[indexB]);
total += Math.abs(difference);
}
}
return total / (double)(rows*columns);
}
/**
*
* Returns the sum of all the pixels in the image.
*
*
* @param img Input image. Not modified.
*/
public static int sum( GrayS8 img ) {
final int rows = img.height;
final int columns = img.width;
int total = 0;
for (int y = 0; y < rows; y++) {
int index = img.startIndex + y * img.stride;
int indexEnd = index+columns;
for (; index < indexEnd; index++ ) {
total += img.data[index] ;
}
}
return total;
}
/**
* Returns the mean pixel intensity value.
*
* @param img Input image. Not modified.
* @return Mean pixel intensity value
*/
public static double mean( GrayS8 img ) {
return sum(img)/(double)(img.width*img.height);
}
/**
*
* Returns the sum of all the pixels in the image.
*
*
* @param img Input image. Not modified.
*/
public static int sum( InterleavedS8 img ) {
final int rows = img.height;
final int columns = img.width*img.numBands;
int total = 0;
for (int y = 0; y < rows; y++) {
int index = img.startIndex + y * img.stride;
int indexEnd = index+columns;
for (; index < indexEnd; index++ ) {
total += img.data[index] ;
}
}
return total;
}
/**
* Returns the mean pixel intensity value.
*
* @param img Input image. Not modified.
* @return Mean pixel intensity value
*/
public static double mean( InterleavedS8 img ) {
return sum(img)/(double)(img.width*img.height*img.numBands);
}
/**
* Computes the variance of pixel intensity values inside the image.
*
* @param img Input image. Not modified.
* @param mean Mean pixel intensity value.
* @return Pixel variance
*/
public static double variance( GrayS8 img , double mean ) {
double variance = 0;
for (int y = 0; y < img.height; y++) {
int index = img.getStartIndex() + y * img.getStride();
int indexEnd = index+img.width;
// for(int x = 0; x < img.width; x++ ) {
for (; index < indexEnd; index++ ) {
double d = (img.data[index]) - mean;
variance += d*d;
}
}
return variance/(img.width*img.height);
}
/**
* Computes the histogram of intensity values for the image.
*
* @param input (input) Image.
* @param minValue (input) Minimum possible intensity value
* @param histogram (output) Storage for histogram. Number of elements must be equal to max value.
*/
public static void histogram( GrayS8 input , int minValue , int histogram[] ) {
for( int i = 0; i < histogram.length; i++ )
histogram[i] = 0;
for( int y = 0; y < input.height; y++ ) {
int index = input.startIndex + y*input.stride;
int end = index + input.width;
for( ; index < end; index++ ) {
histogram[(input.data[index]) - minValue ]++;
}
}
}
/**
* Returns the minimum element value.
*
* @param input Input image. Not modified.
* @return Minimum pixel value.
*/
public static int min( GrayU16 input ) {
return minU( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the minimum element value.
*
* @param input Input image. Not modified.
* @return Minimum pixel value.
*/
public static int min( InterleavedU16 input ) {
return minU( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static int minU( short[] array , int startIndex , int rows , int columns , int stride ) {
int output = array[startIndex]& 0xFFFF;
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
int v = array[index] & 0xFFFF;
if( v < output )
output = v;
}
}
return output;
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static int max( GrayU16 input ) {
return maxU( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static int max( InterleavedU16 input ) {
return maxU( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static int maxU( short[] array , int startIndex , int rows , int columns , int stride ) {
int output = array[startIndex]& 0xFFFF;
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
int v = array[index] & 0xFFFF;
if( v > output )
output = v;
}
}
return output;
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static int maxAbs( GrayU16 input ) {
return maxAbsU( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static int maxAbs( InterleavedU16 input ) {
return maxAbsU( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static int maxAbsU( short[] array , int startIndex , int rows , int columns , int stride ) {
int output = array[startIndex]& 0xFFFF;
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
int v = array[index] & 0xFFFF;
if( v > output )
output = v;
}
}
return output;
}
/**
* Computes the mean squared error (MSE) between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffSq(GrayU16 imgA, GrayU16 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffSqU(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width);
}
/**
* Computes the mean squared error (MSE) between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffSq(InterleavedU16 imgA, InterleavedU16 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffSqU(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width*imgA.numBands);
}
private static double meanDiffSqU(short []dataA, int startIndexA , int strideA,
short []dataB, int startIndexB , int strideB,
int rows , int columns ) {
int total = 0;
for (int y = 0; y < rows; y++) {
int indexA = startIndexA + y * strideA;
int indexB = startIndexB + y * strideB;
int indexEnd = indexA+columns;
for (; indexA < indexEnd; indexA++,indexB++) {
int difference = (dataA[indexA]& 0xFFFF)-(dataB[indexB]& 0xFFFF);
total += difference*difference;
}
}
return total / (double)(rows*columns);
}
/**
* Computes the mean of absolute value error between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffAbs(GrayU16 imgA, GrayU16 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffAbsU(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width);
}
/**
* Computes the mean of absolute value error between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffAbs(InterleavedU16 imgA, InterleavedU16 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffAbsU(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width*imgA.numBands);
}
private static double meanDiffAbsU(short []dataA, int startIndexA , int strideA,
short []dataB, int startIndexB , int strideB,
int rows , int columns ) {
int total = 0;
for (int y = 0; y < rows; y++) {
int indexA = startIndexA + y * strideA;
int indexB = startIndexB + y * strideB;
int indexEnd = indexA+columns;
for (; indexA < indexEnd; indexA++,indexB++) {
int difference = (dataA[indexA]& 0xFFFF)-(dataB[indexB]& 0xFFFF);
total += Math.abs(difference);
}
}
return total / (double)(rows*columns);
}
/**
*
* Returns the sum of all the pixels in the image.
*
*
* @param img Input image. Not modified.
*/
public static int sum( GrayU16 img ) {
final int rows = img.height;
final int columns = img.width;
int total = 0;
for (int y = 0; y < rows; y++) {
int index = img.startIndex + y * img.stride;
int indexEnd = index+columns;
for (; index < indexEnd; index++ ) {
total += img.data[index] & 0xFFFF;
}
}
return total;
}
/**
* Returns the mean pixel intensity value.
*
* @param img Input image. Not modified.
* @return Mean pixel intensity value
*/
public static double mean( GrayU16 img ) {
return sum(img)/(double)(img.width*img.height);
}
/**
*
* Returns the sum of all the pixels in the image.
*
*
* @param img Input image. Not modified.
*/
public static int sum( InterleavedU16 img ) {
final int rows = img.height;
final int columns = img.width*img.numBands;
int total = 0;
for (int y = 0; y < rows; y++) {
int index = img.startIndex + y * img.stride;
int indexEnd = index+columns;
for (; index < indexEnd; index++ ) {
total += img.data[index] & 0xFFFF;
}
}
return total;
}
/**
* Returns the mean pixel intensity value.
*
* @param img Input image. Not modified.
* @return Mean pixel intensity value
*/
public static double mean( InterleavedU16 img ) {
return sum(img)/(double)(img.width*img.height*img.numBands);
}
/**
* Computes the variance of pixel intensity values inside the image.
*
* @param img Input image. Not modified.
* @param mean Mean pixel intensity value.
* @return Pixel variance
*/
public static double variance( GrayU16 img , double mean ) {
double variance = 0;
for (int y = 0; y < img.height; y++) {
int index = img.getStartIndex() + y * img.getStride();
int indexEnd = index+img.width;
// for(int x = 0; x < img.width; x++ ) {
for (; index < indexEnd; index++ ) {
double d = (img.data[index]& 0xFFFF) - mean;
variance += d*d;
}
}
return variance/(img.width*img.height);
}
/**
* Computes the histogram of intensity values for the image.
*
* @param input (input) Image.
* @param minValue (input) Minimum possible intensity value
* @param histogram (output) Storage for histogram. Number of elements must be equal to max value.
*/
public static void histogram( GrayU16 input , int minValue , int histogram[] ) {
for( int i = 0; i < histogram.length; i++ )
histogram[i] = 0;
for( int y = 0; y < input.height; y++ ) {
int index = input.startIndex + y*input.stride;
int end = index + input.width;
for( ; index < end; index++ ) {
histogram[(input.data[index]& 0xFFFF) - minValue ]++;
}
}
}
/**
* Returns the minimum element value.
*
* @param input Input image. Not modified.
* @return Minimum pixel value.
*/
public static int min( GrayS16 input ) {
return min( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the minimum element value.
*
* @param input Input image. Not modified.
* @return Minimum pixel value.
*/
public static int min( InterleavedS16 input ) {
return min( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static int min( short[] array , int startIndex , int rows , int columns , int stride ) {
int output = array[startIndex];
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
int v = array[index] ;
if( v < output )
output = v;
}
}
return output;
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static int max( GrayS16 input ) {
return max( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static int max( InterleavedS16 input ) {
return max( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static int max( short[] array , int startIndex , int rows , int columns , int stride ) {
int output = array[startIndex];
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
int v = array[index] ;
if( v > output )
output = v;
}
}
return output;
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static int maxAbs( GrayS16 input ) {
return maxAbs( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static int maxAbs( InterleavedS16 input ) {
return maxAbs( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static int maxAbs( short[] array , int startIndex , int rows , int columns , int stride ) {
int output = array[startIndex];
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
int v = Math.abs(array[index]);
if( v > output )
output = v;
}
}
return output;
}
/**
* Computes the mean squared error (MSE) between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffSq(GrayS16 imgA, GrayS16 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffSq(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width);
}
/**
* Computes the mean squared error (MSE) between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffSq(InterleavedS16 imgA, InterleavedS16 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffSq(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width*imgA.numBands);
}
private static double meanDiffSq(short []dataA, int startIndexA , int strideA,
short []dataB, int startIndexB , int strideB,
int rows , int columns ) {
int total = 0;
for (int y = 0; y < rows; y++) {
int indexA = startIndexA + y * strideA;
int indexB = startIndexB + y * strideB;
int indexEnd = indexA+columns;
for (; indexA < indexEnd; indexA++,indexB++) {
int difference = (dataA[indexA])-(dataB[indexB]);
total += difference*difference;
}
}
return total / (double)(rows*columns);
}
/**
* Computes the mean of absolute value error between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffAbs(GrayS16 imgA, GrayS16 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffAbs(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width);
}
/**
* Computes the mean of absolute value error between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffAbs(InterleavedS16 imgA, InterleavedS16 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffAbs(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width*imgA.numBands);
}
private static double meanDiffAbs(short []dataA, int startIndexA , int strideA,
short []dataB, int startIndexB , int strideB,
int rows , int columns ) {
int total = 0;
for (int y = 0; y < rows; y++) {
int indexA = startIndexA + y * strideA;
int indexB = startIndexB + y * strideB;
int indexEnd = indexA+columns;
for (; indexA < indexEnd; indexA++,indexB++) {
int difference = (dataA[indexA])-(dataB[indexB]);
total += Math.abs(difference);
}
}
return total / (double)(rows*columns);
}
/**
*
* Returns the sum of all the pixels in the image.
*
*
* @param img Input image. Not modified.
*/
public static int sum( GrayS16 img ) {
final int rows = img.height;
final int columns = img.width;
int total = 0;
for (int y = 0; y < rows; y++) {
int index = img.startIndex + y * img.stride;
int indexEnd = index+columns;
for (; index < indexEnd; index++ ) {
total += img.data[index] ;
}
}
return total;
}
/**
* Returns the mean pixel intensity value.
*
* @param img Input image. Not modified.
* @return Mean pixel intensity value
*/
public static double mean( GrayS16 img ) {
return sum(img)/(double)(img.width*img.height);
}
/**
*
* Returns the sum of all the pixels in the image.
*
*
* @param img Input image. Not modified.
*/
public static int sum( InterleavedS16 img ) {
final int rows = img.height;
final int columns = img.width*img.numBands;
int total = 0;
for (int y = 0; y < rows; y++) {
int index = img.startIndex + y * img.stride;
int indexEnd = index+columns;
for (; index < indexEnd; index++ ) {
total += img.data[index] ;
}
}
return total;
}
/**
* Returns the mean pixel intensity value.
*
* @param img Input image. Not modified.
* @return Mean pixel intensity value
*/
public static double mean( InterleavedS16 img ) {
return sum(img)/(double)(img.width*img.height*img.numBands);
}
/**
* Computes the variance of pixel intensity values inside the image.
*
* @param img Input image. Not modified.
* @param mean Mean pixel intensity value.
* @return Pixel variance
*/
public static double variance( GrayS16 img , double mean ) {
double variance = 0;
for (int y = 0; y < img.height; y++) {
int index = img.getStartIndex() + y * img.getStride();
int indexEnd = index+img.width;
// for(int x = 0; x < img.width; x++ ) {
for (; index < indexEnd; index++ ) {
double d = (img.data[index]) - mean;
variance += d*d;
}
}
return variance/(img.width*img.height);
}
/**
* Computes the histogram of intensity values for the image.
*
* @param input (input) Image.
* @param minValue (input) Minimum possible intensity value
* @param histogram (output) Storage for histogram. Number of elements must be equal to max value.
*/
public static void histogram( GrayS16 input , int minValue , int histogram[] ) {
for( int i = 0; i < histogram.length; i++ )
histogram[i] = 0;
for( int y = 0; y < input.height; y++ ) {
int index = input.startIndex + y*input.stride;
int end = index + input.width;
for( ; index < end; index++ ) {
histogram[(input.data[index]) - minValue ]++;
}
}
}
/**
* Returns the minimum element value.
*
* @param input Input image. Not modified.
* @return Minimum pixel value.
*/
public static int min( GrayS32 input ) {
return min( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the minimum element value.
*
* @param input Input image. Not modified.
* @return Minimum pixel value.
*/
public static int min( InterleavedS32 input ) {
return min( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static int min( int[] array , int startIndex , int rows , int columns , int stride ) {
int output = array[startIndex];
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
int v = array[index] ;
if( v < output )
output = v;
}
}
return output;
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static int max( GrayS32 input ) {
return max( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static int max( InterleavedS32 input ) {
return max( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static int max( int[] array , int startIndex , int rows , int columns , int stride ) {
int output = array[startIndex];
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
int v = array[index] ;
if( v > output )
output = v;
}
}
return output;
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static int maxAbs( GrayS32 input ) {
return maxAbs( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static int maxAbs( InterleavedS32 input ) {
return maxAbs( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static int maxAbs( int[] array , int startIndex , int rows , int columns , int stride ) {
int output = array[startIndex];
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
int v = Math.abs(array[index]);
if( v > output )
output = v;
}
}
return output;
}
/**
* Computes the mean squared error (MSE) between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffSq(GrayS32 imgA, GrayS32 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffSq(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width);
}
/**
* Computes the mean squared error (MSE) between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffSq(InterleavedS32 imgA, InterleavedS32 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffSq(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width*imgA.numBands);
}
private static double meanDiffSq(int []dataA, int startIndexA , int strideA,
int []dataB, int startIndexB , int strideB,
int rows , int columns ) {
int total = 0;
for (int y = 0; y < rows; y++) {
int indexA = startIndexA + y * strideA;
int indexB = startIndexB + y * strideB;
int indexEnd = indexA+columns;
for (; indexA < indexEnd; indexA++,indexB++) {
int difference = (dataA[indexA])-(dataB[indexB]);
total += difference*difference;
}
}
return total / (double)(rows*columns);
}
/**
* Computes the mean of absolute value error between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffAbs(GrayS32 imgA, GrayS32 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffAbs(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width);
}
/**
* Computes the mean of absolute value error between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffAbs(InterleavedS32 imgA, InterleavedS32 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffAbs(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width*imgA.numBands);
}
private static double meanDiffAbs(int []dataA, int startIndexA , int strideA,
int []dataB, int startIndexB , int strideB,
int rows , int columns ) {
int total = 0;
for (int y = 0; y < rows; y++) {
int indexA = startIndexA + y * strideA;
int indexB = startIndexB + y * strideB;
int indexEnd = indexA+columns;
for (; indexA < indexEnd; indexA++,indexB++) {
int difference = (dataA[indexA])-(dataB[indexB]);
total += Math.abs(difference);
}
}
return total / (double)(rows*columns);
}
/**
*
* Returns the sum of all the pixels in the image.
*
*
* @param img Input image. Not modified.
*/
public static int sum( GrayS32 img ) {
final int rows = img.height;
final int columns = img.width;
int total = 0;
for (int y = 0; y < rows; y++) {
int index = img.startIndex + y * img.stride;
int indexEnd = index+columns;
for (; index < indexEnd; index++ ) {
total += img.data[index] ;
}
}
return total;
}
/**
* Returns the mean pixel intensity value.
*
* @param img Input image. Not modified.
* @return Mean pixel intensity value
*/
public static double mean( GrayS32 img ) {
return sum(img)/(double)(img.width*img.height);
}
/**
*
* Returns the sum of all the pixels in the image.
*
*
* @param img Input image. Not modified.
*/
public static int sum( InterleavedS32 img ) {
final int rows = img.height;
final int columns = img.width*img.numBands;
int total = 0;
for (int y = 0; y < rows; y++) {
int index = img.startIndex + y * img.stride;
int indexEnd = index+columns;
for (; index < indexEnd; index++ ) {
total += img.data[index] ;
}
}
return total;
}
/**
* Returns the mean pixel intensity value.
*
* @param img Input image. Not modified.
* @return Mean pixel intensity value
*/
public static double mean( InterleavedS32 img ) {
return sum(img)/(double)(img.width*img.height*img.numBands);
}
/**
* Computes the variance of pixel intensity values inside the image.
*
* @param img Input image. Not modified.
* @param mean Mean pixel intensity value.
* @return Pixel variance
*/
public static double variance( GrayS32 img , double mean ) {
double variance = 0;
for (int y = 0; y < img.height; y++) {
int index = img.getStartIndex() + y * img.getStride();
int indexEnd = index+img.width;
// for(int x = 0; x < img.width; x++ ) {
for (; index < indexEnd; index++ ) {
double d = (img.data[index]) - mean;
variance += d*d;
}
}
return variance/(img.width*img.height);
}
/**
* Computes the histogram of intensity values for the image.
*
* @param input (input) Image.
* @param minValue (input) Minimum possible intensity value
* @param histogram (output) Storage for histogram. Number of elements must be equal to max value.
*/
public static void histogram( GrayS32 input , int minValue , int histogram[] ) {
for( int i = 0; i < histogram.length; i++ )
histogram[i] = 0;
for( int y = 0; y < input.height; y++ ) {
int index = input.startIndex + y*input.stride;
int end = index + input.width;
for( ; index < end; index++ ) {
histogram[(input.data[index]) - minValue ]++;
}
}
}
/**
* Returns the minimum element value.
*
* @param input Input image. Not modified.
* @return Minimum pixel value.
*/
public static long min( GrayS64 input ) {
return min( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the minimum element value.
*
* @param input Input image. Not modified.
* @return Minimum pixel value.
*/
public static long min( InterleavedS64 input ) {
return min( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static long min( long[] array , int startIndex , int rows , int columns , int stride ) {
long output = array[startIndex];
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
long v = array[index] ;
if( v < output )
output = v;
}
}
return output;
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static long max( GrayS64 input ) {
return max( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static long max( InterleavedS64 input ) {
return max( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static long max( long[] array , int startIndex , int rows , int columns , int stride ) {
long output = array[startIndex];
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
long v = array[index] ;
if( v > output )
output = v;
}
}
return output;
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static long maxAbs( GrayS64 input ) {
return maxAbs( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static long maxAbs( InterleavedS64 input ) {
return maxAbs( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static long maxAbs( long[] array , int startIndex , int rows , int columns , int stride ) {
long output = array[startIndex];
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
long v = Math.abs(array[index]);
if( v > output )
output = v;
}
}
return output;
}
/**
* Computes the mean squared error (MSE) between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffSq(GrayS64 imgA, GrayS64 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffSq(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width);
}
/**
* Computes the mean squared error (MSE) between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffSq(InterleavedS64 imgA, InterleavedS64 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffSq(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width*imgA.numBands);
}
private static double meanDiffSq(long []dataA, int startIndexA , int strideA,
long []dataB, int startIndexB , int strideB,
int rows , int columns ) {
long total = 0;
for (int y = 0; y < rows; y++) {
int indexA = startIndexA + y * strideA;
int indexB = startIndexB + y * strideB;
int indexEnd = indexA+columns;
for (; indexA < indexEnd; indexA++,indexB++) {
long difference = (dataA[indexA])-(dataB[indexB]);
total += difference*difference;
}
}
return total / (double)(rows*columns);
}
/**
* Computes the mean of absolute value error between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffAbs(GrayS64 imgA, GrayS64 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffAbs(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width);
}
/**
* Computes the mean of absolute value error between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffAbs(InterleavedS64 imgA, InterleavedS64 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffAbs(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width*imgA.numBands);
}
private static double meanDiffAbs(long []dataA, int startIndexA , int strideA,
long []dataB, int startIndexB , int strideB,
int rows , int columns ) {
long total = 0;
for (int y = 0; y < rows; y++) {
int indexA = startIndexA + y * strideA;
int indexB = startIndexB + y * strideB;
int indexEnd = indexA+columns;
for (; indexA < indexEnd; indexA++,indexB++) {
long difference = (dataA[indexA])-(dataB[indexB]);
total += Math.abs(difference);
}
}
return total / (double)(rows*columns);
}
/**
*
* Returns the sum of all the pixels in the image.
*
*
* @param img Input image. Not modified.
*/
public static long sum( GrayS64 img ) {
final int rows = img.height;
final int columns = img.width;
long total = 0;
for (int y = 0; y < rows; y++) {
int index = img.startIndex + y * img.stride;
int indexEnd = index+columns;
for (; index < indexEnd; index++ ) {
total += img.data[index] ;
}
}
return total;
}
/**
* Returns the mean pixel intensity value.
*
* @param img Input image. Not modified.
* @return Mean pixel intensity value
*/
public static double mean( GrayS64 img ) {
return sum(img)/(double)(img.width*img.height);
}
/**
*
* Returns the sum of all the pixels in the image.
*
*
* @param img Input image. Not modified.
*/
public static long sum( InterleavedS64 img ) {
final int rows = img.height;
final int columns = img.width*img.numBands;
long total = 0;
for (int y = 0; y < rows; y++) {
int index = img.startIndex + y * img.stride;
int indexEnd = index+columns;
for (; index < indexEnd; index++ ) {
total += img.data[index] ;
}
}
return total;
}
/**
* Returns the mean pixel intensity value.
*
* @param img Input image. Not modified.
* @return Mean pixel intensity value
*/
public static double mean( InterleavedS64 img ) {
return sum(img)/(double)(img.width*img.height*img.numBands);
}
/**
* Computes the variance of pixel intensity values inside the image.
*
* @param img Input image. Not modified.
* @param mean Mean pixel intensity value.
* @return Pixel variance
*/
public static double variance( GrayS64 img , double mean ) {
double variance = 0;
for (int y = 0; y < img.height; y++) {
int index = img.getStartIndex() + y * img.getStride();
int indexEnd = index+img.width;
// for(int x = 0; x < img.width; x++ ) {
for (; index < indexEnd; index++ ) {
double d = (img.data[index]) - mean;
variance += d*d;
}
}
return variance/(img.width*img.height);
}
/**
* Computes the histogram of intensity values for the image.
*
* @param input (input) Image.
* @param minValue (input) Minimum possible intensity value
* @param histogram (output) Storage for histogram. Number of elements must be equal to max value.
*/
public static void histogram( GrayS64 input , long minValue , int histogram[] ) {
for( int i = 0; i < histogram.length; i++ )
histogram[i] = 0;
for( int y = 0; y < input.height; y++ ) {
int index = input.startIndex + y*input.stride;
int end = index + input.width;
for( ; index < end; index++ ) {
histogram[(int)(input.data[index] - minValue)]++;
}
}
}
/**
* Returns the minimum element value.
*
* @param input Input image. Not modified.
* @return Minimum pixel value.
*/
public static float min( GrayF32 input ) {
return min( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the minimum element value.
*
* @param input Input image. Not modified.
* @return Minimum pixel value.
*/
public static float min( InterleavedF32 input ) {
return min( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static float min( float[] array , int startIndex , int rows , int columns , int stride ) {
float output = array[startIndex];
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
float v = array[index] ;
if( v < output )
output = v;
}
}
return output;
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static float max( GrayF32 input ) {
return max( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static float max( InterleavedF32 input ) {
return max( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static float max( float[] array , int startIndex , int rows , int columns , int stride ) {
float output = array[startIndex];
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
float v = array[index] ;
if( v > output )
output = v;
}
}
return output;
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static float maxAbs( GrayF32 input ) {
return maxAbs( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static float maxAbs( InterleavedF32 input ) {
return maxAbs( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static float maxAbs( float[] array , int startIndex , int rows , int columns , int stride ) {
float output = array[startIndex];
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
float v = Math.abs(array[index]);
if( v > output )
output = v;
}
}
return output;
}
/**
* Computes the mean squared error (MSE) between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffSq(GrayF32 imgA, GrayF32 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffSq(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width);
}
/**
* Computes the mean squared error (MSE) between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffSq(InterleavedF32 imgA, InterleavedF32 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffSq(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width*imgA.numBands);
}
private static double meanDiffSq(float []dataA, int startIndexA , int strideA,
float []dataB, int startIndexB , int strideB,
int rows , int columns ) {
float total = 0;
for (int y = 0; y < rows; y++) {
int indexA = startIndexA + y * strideA;
int indexB = startIndexB + y * strideB;
int indexEnd = indexA+columns;
for (; indexA < indexEnd; indexA++,indexB++) {
float difference = (dataA[indexA])-(dataB[indexB]);
total += difference*difference;
}
}
return total / (double)(rows*columns);
}
/**
* Computes the mean of absolute value error between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffAbs(GrayF32 imgA, GrayF32 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffAbs(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width);
}
/**
* Computes the mean of absolute value error between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffAbs(InterleavedF32 imgA, InterleavedF32 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffAbs(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width*imgA.numBands);
}
private static double meanDiffAbs(float []dataA, int startIndexA , int strideA,
float []dataB, int startIndexB , int strideB,
int rows , int columns ) {
float total = 0;
for (int y = 0; y < rows; y++) {
int indexA = startIndexA + y * strideA;
int indexB = startIndexB + y * strideB;
int indexEnd = indexA+columns;
for (; indexA < indexEnd; indexA++,indexB++) {
float difference = (dataA[indexA])-(dataB[indexB]);
total += Math.abs(difference);
}
}
return total / (double)(rows*columns);
}
/**
*
* Returns the sum of all the pixels in the image.
*
*
* @param img Input image. Not modified.
*/
public static float sum( GrayF32 img ) {
final int rows = img.height;
final int columns = img.width;
float total = 0;
for (int y = 0; y < rows; y++) {
int index = img.startIndex + y * img.stride;
int indexEnd = index+columns;
for (; index < indexEnd; index++ ) {
total += img.data[index] ;
}
}
return total;
}
/**
* Returns the mean pixel intensity value.
*
* @param img Input image. Not modified.
* @return Mean pixel intensity value
*/
public static float mean( GrayF32 img ) {
return sum(img)/(float)(img.width*img.height);
}
/**
*
* Returns the sum of all the pixels in the image.
*
*
* @param img Input image. Not modified.
*/
public static float sum( InterleavedF32 img ) {
final int rows = img.height;
final int columns = img.width*img.numBands;
float total = 0;
for (int y = 0; y < rows; y++) {
int index = img.startIndex + y * img.stride;
int indexEnd = index+columns;
for (; index < indexEnd; index++ ) {
total += img.data[index] ;
}
}
return total;
}
/**
* Returns the mean pixel intensity value.
*
* @param img Input image. Not modified.
* @return Mean pixel intensity value
*/
public static float mean( InterleavedF32 img ) {
return sum(img)/(float)(img.width*img.height*img.numBands);
}
/**
* Computes the variance of pixel intensity values inside the image.
*
* @param img Input image. Not modified.
* @param mean Mean pixel intensity value.
* @return Pixel variance
*/
public static float variance( GrayF32 img , float mean ) {
float variance = 0;
for (int y = 0; y < img.height; y++) {
int index = img.getStartIndex() + y * img.getStride();
int indexEnd = index+img.width;
// for(int x = 0; x < img.width; x++ ) {
for (; index < indexEnd; index++ ) {
float d = (img.data[index]) - mean;
variance += d*d;
}
}
return variance/(img.width*img.height);
}
/**
* Computes the histogram of intensity values for the image.
*
* @param input (input) Image.
* @param minValue (input) Minimum possible intensity value
* @param histogram (output) Storage for histogram. Number of elements must be equal to max value.
*/
public static void histogram( GrayF32 input , float minValue , int histogram[] ) {
for( int i = 0; i < histogram.length; i++ )
histogram[i] = 0;
for( int y = 0; y < input.height; y++ ) {
int index = input.startIndex + y*input.stride;
int end = index + input.width;
for( ; index < end; index++ ) {
histogram[(int)(input.data[index] - minValue)]++;
}
}
}
/**
* Returns the minimum element value.
*
* @param input Input image. Not modified.
* @return Minimum pixel value.
*/
public static double min( GrayF64 input ) {
return min( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the minimum element value.
*
* @param input Input image. Not modified.
* @return Minimum pixel value.
*/
public static double min( InterleavedF64 input ) {
return min( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static double min( double[] array , int startIndex , int rows , int columns , int stride ) {
double output = array[startIndex];
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
double v = array[index] ;
if( v < output )
output = v;
}
}
return output;
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static double max( GrayF64 input ) {
return max( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static double max( InterleavedF64 input ) {
return max( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static double max( double[] array , int startIndex , int rows , int columns , int stride ) {
double output = array[startIndex];
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
double v = array[index] ;
if( v > output )
output = v;
}
}
return output;
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static double maxAbs( GrayF64 input ) {
return maxAbs( input.data, input.startIndex, input.height, input.width , input.stride );
}
/**
* Returns the maximum element value.
*
* @param input Input image. Not modified.
* @return Maximum pixel value.
*/
public static double maxAbs( InterleavedF64 input ) {
return maxAbs( input.data, input.startIndex, input.height, input.width*input.numBands , input.stride );
}
private static double maxAbs( double[] array , int startIndex , int rows , int columns , int stride ) {
double output = array[startIndex];
for( int y = 0; y < rows; y++ ) {
int index = startIndex + y*stride;
int end = index + columns;
for( ; index < end; index++ ) {
double v = Math.abs(array[index]);
if( v > output )
output = v;
}
}
return output;
}
/**
* Computes the mean squared error (MSE) between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffSq(GrayF64 imgA, GrayF64 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffSq(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width);
}
/**
* Computes the mean squared error (MSE) between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffSq(InterleavedF64 imgA, InterleavedF64 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffSq(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width*imgA.numBands);
}
private static double meanDiffSq(double []dataA, int startIndexA , int strideA,
double []dataB, int startIndexB , int strideB,
int rows , int columns ) {
double total = 0;
for (int y = 0; y < rows; y++) {
int indexA = startIndexA + y * strideA;
int indexB = startIndexB + y * strideB;
int indexEnd = indexA+columns;
for (; indexA < indexEnd; indexA++,indexB++) {
double difference = (dataA[indexA])-(dataB[indexB]);
total += difference*difference;
}
}
return total / (double)(rows*columns);
}
/**
* Computes the mean of absolute value error between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffAbs(GrayF64 imgA, GrayF64 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffAbs(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width);
}
/**
* Computes the mean of absolute value error between the two images.
*
* @param imgA first image. Not modified.
* @param imgB second image. Not modified.
* @return error between the two images.
*/
public static double meanDiffAbs(InterleavedF64 imgA, InterleavedF64 imgB ) {
InputSanityCheck.checkSameShape(imgA,imgB);
return meanDiffAbs(imgA.data,imgA.startIndex,imgA.stride, imgB.data,imgB.startIndex,imgB.stride,
imgA.height, imgA.width*imgA.numBands);
}
private static double meanDiffAbs(double []dataA, int startIndexA , int strideA,
double []dataB, int startIndexB , int strideB,
int rows , int columns ) {
double total = 0;
for (int y = 0; y < rows; y++) {
int indexA = startIndexA + y * strideA;
int indexB = startIndexB + y * strideB;
int indexEnd = indexA+columns;
for (; indexA < indexEnd; indexA++,indexB++) {
double difference = (dataA[indexA])-(dataB[indexB]);
total += Math.abs(difference);
}
}
return total / (double)(rows*columns);
}
/**
*
* Returns the sum of all the pixels in the image.
*
*
* @param img Input image. Not modified.
*/
public static double sum( GrayF64 img ) {
final int rows = img.height;
final int columns = img.width;
double total = 0;
for (int y = 0; y < rows; y++) {
int index = img.startIndex + y * img.stride;
int indexEnd = index+columns;
for (; index < indexEnd; index++ ) {
total += img.data[index] ;
}
}
return total;
}
/**
* Returns the mean pixel intensity value.
*
* @param img Input image. Not modified.
* @return Mean pixel intensity value
*/
public static double mean( GrayF64 img ) {
return sum(img)/(double)(img.width*img.height);
}
/**
*
* Returns the sum of all the pixels in the image.
*
*
* @param img Input image. Not modified.
*/
public static double sum( InterleavedF64 img ) {
final int rows = img.height;
final int columns = img.width*img.numBands;
double total = 0;
for (int y = 0; y < rows; y++) {
int index = img.startIndex + y * img.stride;
int indexEnd = index+columns;
for (; index < indexEnd; index++ ) {
total += img.data[index] ;
}
}
return total;
}
/**
* Returns the mean pixel intensity value.
*
* @param img Input image. Not modified.
* @return Mean pixel intensity value
*/
public static double mean( InterleavedF64 img ) {
return sum(img)/(double)(img.width*img.height*img.numBands);
}
/**
* Computes the variance of pixel intensity values inside the image.
*
* @param img Input image. Not modified.
* @param mean Mean pixel intensity value.
* @return Pixel variance
*/
public static double variance( GrayF64 img , double mean ) {
double variance = 0;
for (int y = 0; y < img.height; y++) {
int index = img.getStartIndex() + y * img.getStride();
int indexEnd = index+img.width;
// for(int x = 0; x < img.width; x++ ) {
for (; index < indexEnd; index++ ) {
double d = (img.data[index]) - mean;
variance += d*d;
}
}
return variance/(img.width*img.height);
}
/**
* Computes the histogram of intensity values for the image.
*
* @param input (input) Image.
* @param minValue (input) Minimum possible intensity value
* @param histogram (output) Storage for histogram. Number of elements must be equal to max value.
*/
public static void histogram( GrayF64 input , double minValue , int histogram[] ) {
for( int i = 0; i < histogram.length; i++ )
histogram[i] = 0;
for( int y = 0; y < input.height; y++ ) {
int index = input.startIndex + y*input.stride;
int end = index + input.width;
for( ; index < end; index++ ) {
histogram[(int)(input.data[index] - minValue)]++;
}
}
}
}