Matching colors between two pictures in OpenCV?

edit

maybe a simple mean subtraction will already get you close:

Scalar m1,d1;
meanStdDev(im1,m1,d1); // "lower"

Scalar m2,d2;
meanStdDev(img2,m2,d2); //"upper"

cerr << m1 << d1 << endl;
cerr << m2 << d2 << endl;

Scalar mdiff = m1-m2;

img1 -= mdiff;

Scalar m3,d3;
meanStdDev(img1 ,m3, d3);
cerr << m3 << d3 << endl;


[128.965, 129.764, 131.6, 0][61.9842, 62.0493, 57.8344, 0]   // img1
[44.4416, 79.0048, 72.5779, 0][16.5399, 34.9685, 31.0255, 0] // img2
[53.9764, 82.1853, 77.0983, 0][48.514, 56.5164, 49.9328, 0]  // result

i have copied the following code from a previous answer by @berak

    Mat src = imread("iO6S1m.png");
    Mat dst = imread("kfku3m.png");

    Mat src = imread("kfku3m.png");
    Mat dst= imread("iO6S1m.png");

#include <opencv2/opencv.hpp>
using namespace cv;

#include <vector>
using namespace std;

#define HISTMATCH_EPSILON 0.000001
#define BTM_DEBUG
// Compute histogram and CDF for an image with mask
void do1ChnHist(const Mat_<uchar> &img, const Mat_<uchar> &mask, Mat_<double> &h, Mat_<double> &cdf)
{
    for (size_t p = 0; p<img.total(); p++)
    {
        if (mask(p) > 0)
        {
            uchar c = img(p);
            h(c) += 1.0;
        }
    }

    normalize(h, h, 1, 0, NORM_MINMAX);

    cdf(0) = h(0);
    for (int j = 1; j<256; j++)
    {
        cdf(j) = cdf(j - 1) + h(j);
    }

    normalize(cdf, cdf, 1, 0, NORM_MINMAX);
}

// match histograms of 'src' to that of 'dst', according to both masks
void histMatchRGB(Mat &src, const Mat &src_mask, const Mat &dst, const Mat &dst_mask)
{
#ifdef BTM_DEBUG
    namedWindow("original source", CV_WINDOW_AUTOSIZE);
    imshow("original source", src);
    namedWindow("original query", CV_WINDOW_AUTOSIZE);
    imshow("original query", dst);
#endif

    vector<Mat_<uchar>> chns, chns1;
    split(src, chns);
    split(dst, chns1);

    for (int i = 0; i<3; i++)
    {
        Mat_<double> src_hist = Mat_<double>::zeros(1, 256);
        Mat_<double> dst_hist = Mat_<double>::zeros(1, 256);
        Mat_<double> src_cdf = Mat_<double>::zeros(1, 256);
        Mat_<double> dst_cdf = Mat_<double>::zeros(1, 256);

        do1ChnHist(chns[i], src_mask, src_hist, src_cdf);
        do1ChnHist(chns1[i], dst_mask, dst_hist, dst_cdf);

        uchar last = 0;

        Mat_<uchar> lut(1, 256);
        for (int j = 0; j<src_cdf.cols; j++)
        {
            double F1j = src_cdf(j);

            for (uchar k = last; k<dst_cdf.cols; k++)
            {
                double F2k = dst_cdf(k);
                if (abs(F2k - F1j) < HISTMATCH_EPSILON || F2k > F1j)
                {
                    lut(j) = k;
                    last = k;
                    break;
                }
            }
        }

        LUT(chns[i], lut, chns[i]);
    }

    Mat res;
    merge(chns, res);

#ifdef BTM_DEBUG
    namedWindow("matched", CV_WINDOW_AUTOSIZE);
    imshow("matched", res);

    waitKey(0);
#endif

    res.copyTo(src);
}

int main(int argc, char **argv)
{
    Mat src = imread("e:/test/iO6S1m.png");
    Mat dst = imread("e:/test/kfku3m.png");
    Mat mask = Mat(src.size(), CV_8U, Scalar(255));

    histMatchRGB(dst, mask, src, mask);
    return 0;
}