OpenCV小项目：图像融合（泊松融合—Possion Blending）
作者：互联网
原理
太多了，看这些博客吧
主要参考博客1: http://blog.csdn.net/hjimce/article/details/45716603
主要参考博客2: http://blog.csdn.net/wd1603926823/article/details/49867069
主要参考博客3: http://blog.csdn.net/baimafujinji/article/details/46787837
代码示例
#include <iostream>
#include <math.h>
#include <opencv2/opencv.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/highgui/highgui_c.h>
using namespace std;
using namespace cv;
#define elif else if
#define ATD at<double>
// 图像水平梯度的正向计算，即img（i，j+1）-img（i，j）
// img：要计算其梯度的图像
Mat getGradientXp(Mat &img)
{
int height = img.rows;
int width = img.cols;
Mat casimg = repeat(img, 1, 2); // repeat the input img for two times, they are horizontally arranged.
Rect roi = Rect(1, 0, width, height);
Mat roimat = casimg(roi); // roimat is the version of img that the first column is in the last one, the other columns move one column forward.
return roimat - img; // img(i, j + 1) - img(i, j)
}
// 图像垂直梯度的正向计算，即img（i+1，j）-img（i，j）
// img：要计算其梯度的图像
Mat getGradientYp(Mat &img)
{
int height = img.rows;
int width = img.cols;
Mat casimg = repeat(img, 2, 1); // repeat the input img for two times, they are vertically arranged.
Rect roi = Rect(0, 1, width, height);
Mat roimat = casimg(roi); // roimat is the version of img that the first row is in the last one, the other rows move one row forward.
return roimat - img; // img(i + 1, j) - img(i, j)
}
// 图像水平梯度的负向计算，即img（i，j-1）-img（i，j）
// img：要计算其梯度的图像
Mat getGradientXn(Mat &img) {
int height = img.rows;
int width = img.cols;
Mat casimg = repeat(img, 1, 2); // repeat the input img for two times, they are horizontally arranged.
Rect roi = Rect(width - 1, 0, width, height);
Mat roimat = casimg(roi); // roimat is the version of img that the last column is in the first one, the other columns move one column backward.
return roimat - img; // img(i, j - 1) - img(i, j)
}
// 图像垂直梯度的负向计算，即img（i-1，j）-img（i，j）
// img：要计算其梯度的图像
Mat getGradientYn(Mat &img)
{
int height = img.rows;
int width = img.cols;
Mat casimg = repeat(img, 2, 1); // repeat the input img for two times, they are vertically arranged.
Rect roi = Rect(0, height - 1, width, height);
Mat roimat = casimg(roi); // roimat is the version of img that the last row is in the first one, the other rows move one row backward.
return roimat - img; // img(i - 1, j) - img(i, j)
}
int getLabel(int i, int j, int height, int width)
{
return i * width + j; // i is in height axis; j is in width axis.
}
// 得到矩阵A
Mat getA(int height, int width)
{
Mat A = Mat::eye(height * width, height * width, CV_64FC1);
A *= -4;
// M: the label matrix of roi from im2; divede M into three parts, 0,1,2, respectively.
// 0: the corners of roi
// 1: boundaries but not corners
// 2: inner part of roi
// different parts represent different methods to asssign A values
Mat M = Mat::zeros(height, width, CV_64FC1);
Mat temp = Mat::ones(height, width - 2, CV_64FC1);
Rect roi = Rect(1, 0, width - 2, height);
Mat roimat = M(roi);
temp.copyTo(roimat);
temp = Mat::ones(height - 2, width, CV_64FC1);
roi = Rect(0, 1, width, height - 2);
roimat = M(roi);
temp.copyTo(roimat);
temp = Mat::ones(height - 2, width - 2, CV_64FC1);
temp *= 2;
roi = Rect(1, 1, width - 2, height - 2);
roimat = M(roi);
temp.copyTo(roimat);
// get Matrix A
for (int i = 0; i < height; i++) {
for (int j = 0; j < width; j++) {
// get index of M(i,j)
int label = getLabel(i, j, height, width);
// when M(i,j) is the corner, assign coeffients to A
if (M.ATD(i, j) == 0)
{
if (i == 0) A.ATD(getLabel(i + 1, j, height, width), label) = 1; // left upper
elif(i == height - 1) A.ATD(getLabel(i - 1, j, height, width), label) = 1; // right upper
if (j == 0) A.ATD(getLabel(i, j + 1, height, width), label) = 1; // left lower
elif(j == width - 1) A.ATD(getLabel(i, j - 1, height, width), label) = 1; // right lower
}
// when M(i,j) is the boundary but not corner, assign coeffients to A
elif(M.ATD(i, j) == 1)
{
if (i == 0) {
A.ATD(getLabel(i + 1, j, height, width), label) = 1;
A.ATD(getLabel(i, j - 1, height, width), label) = 1;
A.ATD(getLabel(i, j + 1, height, width), label) = 1;
}elif(i == height - 1) {
A.ATD(getLabel(i - 1, j, height, width), label) = 1;
A.ATD(getLabel(i, j - 1, height, width), label) = 1;
A.ATD(getLabel(i, j + 1, height, width), label) = 1;
}
if (j == 0) {
A.ATD(getLabel(i, j + 1, height, width), label) = 1;
A.ATD(getLabel(i - 1, j, height, width), label) = 1;
A.ATD(getLabel(i + 1, j, height, width), label) = 1;
}elif(j == width - 1) {
A.ATD(getLabel(i, j - 1, height, width), label) = 1;
A.ATD(getLabel(i - 1, j, height, width), label) = 1;
A.ATD(getLabel(i + 1, j, height, width), label) = 1;
}
}
// when M(i,j) is the inner point, assign coeffients to A
else {
A.ATD(getLabel(i, j - 1, height, width), label) = 1;
A.ATD(getLabel(i, j + 1, height, width), label) = 1;
A.ATD(getLabel(i - 1, j, height, width), label) = 1;
A.ATD(getLabel(i + 1, j, height, width), label) = 1;
}
}
}
return A;
}
// 计算b
// 使用getGradient函数。
Mat getB2(Mat &img1, Mat &img2, int posX, int posY, Rect ROI)
{
// calculate the divergence of img1
Mat MergeGradXp = getGradientXp(img1);
Mat GradXp2 = getGradientXp(img2);
Mat MergeGradXpROI = MergeGradXp(ROI);
GradXp2.copyTo(MergeGradXpROI);
Mat MergeGradXn = getGradientXn(img1);
Mat GradXn2 = getGradientXn(img2);
Mat MergeGradXnROI = MergeGradXn(ROI);
GradXn2.copyTo(MergeGradXnROI);
Mat MergeGradYp = getGradientYp(img1);
Mat GradYp2 = getGradientYp(img2);
Mat MergeGradYpROI = MergeGradYp(ROI);
GradYp2.copyTo(MergeGradYpROI);
Mat MergeGradYn = getGradientYn(img1);
Mat GradYn2 = getGradientYn(img2);
Mat MergeGradYnROI = MergeGradYn(ROI);
GradYn2.copyTo(MergeGradYnROI);
Mat grad = MergeGradXp + MergeGradXn + MergeGradYp + MergeGradYn;
int roiheight = ROI.height;
int roiwidth = ROI.width;
Mat B = Mat::zeros(roiheight * roiwidth, 1, CV_64FC1);
for (int i = 0; i < roiheight; i++) {
for (int j = 0; j < roiwidth; j++) {
double temp = 0.0;
temp += grad.ATD(i + ROI.y, j + ROI.x);
if (i == 0) temp -= img2.ATD(i - 1 + posY, j + posX);
if (i == roiheight - 1) temp -= img2.ATD(i + 1 + posY, j + posX);
if (j == 0) temp -= img2.ATD(i + posY, j - 1 + posX);
if (j == roiwidth - 1) temp -= img2.ATD(i + posY, j + 1 + posX);
B.ATD(getLabel(i, j, roiheight, roiwidth), 0) = temp;
}
}
return B;
}
// 求解方程，并将其重塑为正确的高度和宽度。
// Solve equation and reshape it back to the right height and width.
Mat getResult(Mat &A, Mat &B, Rect &ROI) {
Mat result;
solve(A, B, result);
result = result.reshape(0, ROI.height);
return result;
}
/// 泊松混合
// img1: 3-channel image, we wanna move something in it into img2.
// img2: 3-channel image, dst image.
// ROI: the position and size of the block we want to move in img1.
// posX, posY: where we want to move the block to in img2
Mat poisson_blending(Mat &img1, Mat &img2, Rect ROI, int posX, int posY)
{
int roiheight = ROI.height;
int roiwidth = ROI.width;
Mat A = getA(roiheight, roiwidth);
// we must do the poisson blending to each channel.
vector<Mat> rgb1;
split(img1, rgb1);
vector<Mat> rgb2;
split(img2, rgb2);
vector<Mat> result;
Mat merged, res, Br, Bg, Bb;
Br = getB2(rgb1[0], rgb2[0], posX, posY, ROI);
res = getResult(A, Br, ROI);
result.push_back(res);
cout << "R channel finished..." << endl;
Bg = getB2(rgb1[1], rgb2[1], posX, posY, ROI);
res = getResult(A, Bg, ROI);
result.push_back(res);
cout << "G channel finished..." << endl;
Bb = getB2(rgb1[2], rgb2[2], posX, posY, ROI);
res = getResult(A, Bb, ROI);
result.push_back(res);
cout << "B channel finished..." << endl;
// merge the 3 gray images into a 3-channel image
merge(result, merged);
return merged;
}
int main(int argc, char** argv)
{
Mat img1, img2;
Mat in1 = imread("./image/niao.jpg");
Mat in2 = imread("./image/park.jpg");
imshow("src", in1);
imshow("dst", in2);
in1.convertTo(img1, CV_64FC3);
in2.convertTo(img2, CV_64FC3);
Rect rc = Rect(50, 62, 74, 38);//the part in im2 that we wanna move into im1
// img1: 3-channel image, we wanna move something in it into img2.
// img2: 3-channel image, dst image.
// ROI: the position and size of the block we want to move in img1.
// posX, posY: where we want to move the block to in img2
Mat result = poisson_blending(img1, img2, rc, 90, 60);
result.convertTo(result, CV_8UC1);
Rect rc2 = Rect(400, 50, 74, 38);
Mat roimat = in2(rc2);
result.copyTo(roimat);
imshow("roi", result);
imshow("result", in2);
imwrite("./image/niao_park.jpg", in2);
waitKey(0);
return 0;
}
标签：泊松,Mat,img,int,融合,height,width,Blending,ATD 来源： https://blog.csdn.net/weixin_45525272/article/details/122718252