我有两个不同的图像（图像A和图像B），其直方图（histImage和histImage1）已经计算过了。 现在我希望图像A的直方图成为图像B的直方图。因此图像B获得与图像A类似的颜色。 代码如下：
#include "stdafx.h"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
using namespace std;
using namespace cv;
int main( )
{
Mat src, dst, src1;
/// Load image
src = imread("ImageA", 1 ); // Image A
src1 = imread("ImageB", 1 ); // Image B
if( !src.data )
{ return -1; }
/// Separate the image in 3 places ( B, G and R )
vector<Mat> bgr_planes;
vector<Mat> bgr_planes1;
split( src, bgr_planes );
split( src1, bgr_planes1 );
/// Establish the number of bins
int histSize = 256;
/// Set the ranges ( for B,G,R) )
float range[] = { 0, 256 } ;
const float* histRange = { range };
bool uniform = true; bool accumulate = false;
Mat b_hist, g_hist, r_hist; //ImageA
Mat b_hist1, g_hist1, r_hist1; //ImageB
/// Compute the histograms of Image A
calcHist( &bgr_planes[0], 1, 0, Mat(), b_hist, 1, &histSize, &histRange, uniform, accumulate );
calcHist( &bgr_planes[1], 1, 0, Mat(), g_hist, 1, &histSize, &histRange, uniform, accumulate );
calcHist( &bgr_planes[2], 1, 0, Mat(), r_hist, 1, &histSize, &histRange, uniform, accumulate );
/// Compute the histograms of Image B
calcHist( &bgr_planes1[0], 1, 0, Mat(), b_hist1, 1, &histSize, &histRange, uniform, accumulate );
calcHist( &bgr_planes1[1], 1, 0, Mat(), g_hist1, 1, &histSize, &histRange, uniform, accumulate );
calcHist( &bgr_planes1[2], 1, 0, Mat(), r_hist1, 1, &histSize, &histRange, uniform, accumulate );
// Draw the histograms for B, G and R
int hist_w = 512; int hist_h = 400; //Image A
int bin_w = cvRound( (double) hist_w/histSize ); //Image A
int hist_w1 = 512; int hist_h1 = 400; //Image B
int bin_w1 = cvRound( (double) hist_w1/histSize );//Image B
Mat histImage( hist_h, hist_w, CV_8UC3, Scalar( 0,0,0) ); //ImageA
Mat histImage1( hist_h1, hist_w1, CV_8UC3, Scalar( 0,0,0) ); //ImageB
/// Normalize the result to [ 0, histImage.rows ] ImageA
normalize(b_hist, b_hist, 0, histImage.rows, NORM_MINMAX, -1, Mat() );
normalize(g_hist, g_hist, 0, histImage.rows, NORM_MINMAX, -1, Mat() );
normalize(r_hist, r_hist, 0, histImage.rows, NORM_MINMAX, -1, Mat() );
/// Normalize the result to [ 0, histImage.rows ] ImageB
normalize(b_hist1, b_hist1, 0, histImage.rows, NORM_MINMAX, -1, Mat() );
normalize(g_hist1, g_hist1, 0, histImage.rows, NORM_MINMAX, -1, Mat() );
normalize(r_hist1, r_hist1, 0, histImage.rows, NORM_MINMAX, -1, Mat() );
/// Draw for each channel ImageA
for( int i = 1; i < histSize; i++ )
{
line( histImage, Point( bin_w*(i-1), hist_h - cvRound(b_hist.at<float>(i-1)) ) ,
Point( bin_w*(i), hist_h - cvRound(b_hist.at<float>(i)) ),
Scalar( 255, 0, 0), 2, 8, 0 );
line( histImage, Point( bin_w*(i-1), hist_h - cvRound(g_hist.at<float>(i-1)) ) ,
Point( bin_w*(i), hist_h - cvRound(g_hist.at<float>(i)) ),
Scalar( 0, 255, 0), 2, 8, 0 );
line( histImage, Point( bin_w*(i-1), hist_h - cvRound(r_hist.at<float>(i-1)) ) ,
Point( bin_w*(i), hist_h - cvRound(r_hist.at<float>(i)) ),
Scalar( 0, 0, 255), 2, 8, 0 );
}
////////////////////////////////////////////////////
/// Draw for each channel ImageB
for( int i = 1; i < histSize; i++ )
{
line( histImage1, Point( bin_w1*(i-1), hist_h1 - cvRound(b_hist1.at<float>(i-1)) ) ,
Point( bin_w1*(i), hist_h1 - cvRound(b_hist1.at<float>(i)) ),
Scalar( 255, 0, 0), 2, 8, 0 );
line( histImage1, Point( bin_w1*(i-1), hist_h1 - cvRound(g_hist1.at<float>(i-1)) ) ,
Point( bin_w1*(i), hist_h1 - cvRound(g_hist1.at<float>(i)) ),
Scalar( 0, 255, 0), 2, 8, 0 );
line( histImage1, Point( bin_w1*(i-1), hist_h1 - cvRound(r_hist1.at<float>(i-1)) ) ,
Point( bin_w1*(i), hist_h1 - cvRound(r_hist1.at<float>(i)) ),
Scalar( 0, 0, 255), 2, 8, 0 );
}
/////////////////////////////////////////////////////
/// Display
namedWindow("calcHist", CV_WINDOW_AUTOSIZE );
imshow("face ", histImage ); //Histogram of Image A
/// Display
namedWindow("calcHist1", CV_WINDOW_AUTOSIZE );
imshow("body ", histImage1 ); //Histogram of Image B
waitKey(0);
return 0;
}