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blending.cpp

@@ -0,0 +1,125 @@
+#include <opencv2\opencv.hpp>
+#include <opencv2\stitching.hpp>
+#include <time.h>
+#include <tchar.h>
+
+#define DEBUG 1
+
+using namespace std;
+using namespace cv;
+
+#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);
+
+
+    res.copyTo(src);
+}
+
+
+int _tmain(int argc, _TCHAR* argv[])
+{
+    vector<Mat> images;
+    Mat matLeftImage;
+    Mat matRightImage;
+
+    matLeftImage = imread("3.jpg", IMREAD_COLOR);
+    matRightImage = imread("6.jpg", IMREAD_COLOR);
+
+    Mat mask = Mat(matLeftImage.size(), CV_8U, Scalar(255));
+
+    histMatchRGB(matRightImage, mask, matLeftImage, mask);
+
+    images.push_back(matLeftImage);
+    images.push_back(matRightImage);
+
+    Mat result;
+
+    Stitcher stitcher = Stitcher::createDefault();
+
+    int ok = stitcher.stitch(images, result);
+
+    cout << ok << "        " << stitcher.OK << endl;
+    if (ok == stitcher.OK)
+    {
+        imshow("Result", result);
+        waitKey(0);
+    }
+    else
+    {
+        cout << "Fail Stitching" << endl;
+    }
+
+    return 0;
+
+}