vs2015+opencv3.3.1 +Eigen 3.3.4 c++实现 薄膜插值 泊松图像编辑（v=0||Δf=0）

#include "core/core.hpp"
#include "highgui/highgui.hpp"
#include "imgproc/imgproc.hpp"
#include "iostream"
#include <Eigen/Sparse>
using namespace std;
using namespace cv;
using namespace Eigen;

int main()
{
	const string File = "789.jpg";
	Mat imageSource = imread(File, 0);
	for (unsigned int i = 0; i < imageSource.rows; i++)
		for (unsigned j = 0; j < imageSource.cols; j++)
			if (imageSource.at<uchar>(i, j) != 0)imageSource.at<uchar>(i, j) = 255;
	namedWindow("Source Image");
	imshow("Source Image", imageSource);

	Mat image;
	GaussianBlur(imageSource, image, Size(15, 15), 0);
	Canny(image, image, 100, 250);
	vector<vector<Point>> contours;
	vector<Vec4i> hierarchy;
	findContours(image, contours, hierarchy, RETR_LIST, CHAIN_APPROX_NONE, Point());
	Mat imageContours = Mat::zeros(image.size(), CV_8UC1);
	Mat Contours = Mat::zeros(image.size(), CV_8UC1);  //绘制
													   //contours[i]代表的是第i个轮廓，contours[i].size()代表的是第i个轮廓上所有的像素点数
	int cont_area_M = 0;
	for (int i = 0; i < contours.size(); i++) {
		if (contourArea(contours[i])>cont_area_M)
			cont_area_M = contourArea(contours[i]);
		for (int j = 0; j < contours[i].size(); j++)
		{
			//绘制出contours向量内所有的像素点
			Point P = Point(contours[i][j].x, contours[i][j].y);
			Contours.at<uchar>(P) = 255;

		}
	}
	//绘制轮廓  

	auto itc = contours.begin();

	while (itc != contours.end())
	{
		if (contourArea(*itc)<cont_area_M - 1)
			itc = contours.erase(itc);
		else
			++itc;

	}

	drawContours(imageContours, contours, 0, Scalar(255), 1, 8, hierarchy, 0);

	Rect rect = boundingRect(contours[0]);

	Mat ima = imread("7892.jpg", 1);

	Point p1(0, 0);

	int n = 0;

	SparseMatrix< double, ColMajor> src1((rect.height + 2)*(rect.width + 2), (rect.height + 2)*(rect.width + 2));
	VectorXd src20((rect.height + 2)*(rect.width + 2));
	VectorXd src21((rect.height + 2)*(rect.width + 2));
	VectorXd src22((rect.height + 2)*(rect.width + 2));

	for (int i = rect.y - 1; i < rect.height + rect.y + 1; i++)
		for (int j = rect.x - 1; j < rect.width + rect.x + 1; j++)
		{
			p1.x = j; p1.y = i;
			if (pointPolygonTest(contours[0], p1, false) >0)
			{
				src1.insert(n, n) = 4;
				src1.insert(n, n - 1) = -1;
				src1.insert(n, n + 1) = -1;
				src1.insert(n, n - rect.width - 2) = -1;
				src1.insert(n, n + rect.width + 2) = -1;
				src20(n) = 0;
				src21(n) = 0;
				src22(n) = 0;
			}
			else {
				src1.insert(n, n) = 1;
				src20(n) = ima.at<Vec3b>(p1)[0];
				src21(n) = ima.at<Vec3b>(p1)[1];
				src22(n) = ima.at<Vec3b>(p1)[2];

			};
			++n;
		}
	//	cout << src1;

	VectorXd dst00; VectorXd dst01; VectorXd dst02;
	SparseLU <SparseMatrix <double, ColMajor>>  solver;
	solver.analyzePattern(src1);
	solver.factorize(src1);
	dst00 = solver.solve(src20);
	dst01 = solver.solve(src21);
	dst02 = solver.solve(src22);

	n = 0;

	for (int i = rect.y - 1; i < rect.height + rect.y + 1; i++)
		for (int j = rect.x - 1; j < rect.width + rect.x + 1; j++) {
			ima.at<Vec3b>(i, j)[0] = dst00(n);
			ima.at<Vec3b>(i, j)[1] = dst01(n);
			ima.at<Vec3b>(i, j)[2] = dst02(n);
			n++;
		}

	imshow("Contours Image", imageContours); //轮廓
	imshow("Point of Contours", Contours);   //向量contours内保存的所有轮廓点集
	imshow("Poin", ima);
	waitKey(0);

	system("pause");
	return 0;
}

　789.jpg　

7892.jpg

结果

大概十几s到40s出结果。