#include <opencv2\opencv.hpp>
#include <opencv2\highgui\highgui.hpp>#include <opencv2\imgcodecs\imgcodecs.hpp>#include<iostream>#include<vector>#include<algorithm>#include<math.h>#include<iomanip>void salt(cv::Mat image, int n);void pepper(cv::Mat image, int n);void medeanFilter(cv::Mat& src, int win_size);void meanFilter(cv::Mat& src, int size);using namespace cv;using namespace std;//int Max(vector<uchar> Array, int size);void Open(Mat& src,Mat& img, int size);//int Min(vector<uchar> Array1, int size);void Close(Mat& src, Mat& img, int size);int main() { Mat img= imread("2.jpg"); Mat image = imread("2.jpg");//原图 imshow("原图",image);//salt(image, 3000);//加入盐噪声255
//pepper(image, 3000);//加入椒噪声0 //imshow("椒盐噪声", image);//椒盐噪声图片//medeanFilter(image, 3);
//imshow("中值滤波",image);//中值滤波图片//meanFilter(image,3);
//imshow("均值滤波",image);//均值滤波图片Open(image,img,3);
imshow("开运算-膨胀", img);//膨胀//Close(image, img,3);
//imshow("闭运算-腐蚀",img);//腐蚀waitKey(0);
return 0;
}
void salt(Mat image, int n) {int i, j;
for (int k = 0; k<n / 2; k++) {i = rand() % image.cols; // % 整除取余数运算符,rand=1022,cols=1000,rand%cols=22
j = rand() % image.rows;if (image.type() == CV_8UC1) { // gray-level image
image.at<uchar>(j, i) = 255; //at方法需要指定Mat变量返回值类型,如uchar等
}
else if (image.type() == CV_8UC3) { // color imageimage.at<Vec3b>(j, i)[0] = 255; //cv::Vec3b为opencv定义的一个3个值的向量类型
image.at<Vec3b>(j, i)[1] = 255; //[]指定通道，B:0，G:1，R:2 image.at<Vec3b>(j, i)[2] = 255; } }}void pepper(cv::Mat image, int n) {
int i, j; for (int k = 0; k < n; k++) {// rand() is the random number generator
i = rand() % image.cols; // % 整除取余数运算符,rand=1022,cols=1000,rand%cols=22 j = rand() % image.rows;if (image.type() == CV_8UC1) { // gray-level image
image.at<uchar>(j, i) = 0; //at方法需要指定Mat变量返回值类型,如uchar等
}
else if (image.type() == CV_8UC3) { // color imageimage.at<Vec3b>(j, i)[0] = 0; //cv::Vec3b为opencv定义的一个3个值的向量类型
image.at<Vec3b>(j, i)[1] = 0; //[]指定通道，B:0，G:1，R:2 image.at<Vec3b>(j, i)[2] = 0; } }}//中值滤波
void medeanFilter(Mat& src, int size) { int row = src.rows, col= src.cols; int start = size / 2; for (int m = start; m <row - start; m++) { for (int n = start; n < col - start; n++) { vector<uchar> Array; for (int i = -start + m; i <= start + m; i++) { for (int j = -start + n; j <= start + n; j++) { Array.push_back(src.at<Vec3b>(i, j)[0]); } } sort(Array.begin(), Array.end());//快速排序 src.at<Vec3b>(m, n)[0] = Array[size*size / 2]; }for (int n = start; n < col - start; n++) {
vector<uchar> Array; for (int i = -start + m; i <= start + m; i++) { for (int j = -start + n; j <= start + n; j++) { Array.push_back(src.at<Vec3b>(i, j)[1]); } } sort(Array.begin(), Array.end()); src.at<Vec3b>(m, n)[1] = Array[size*size / 2]; }for (int n = start; n < col - start; n++) {
vector<uchar> Array; for (int i = -start + m; i <= start + m; i++) { for (int j = -start + n; j <= start + n; j++) { Array.push_back(src.at<Vec3b>(i, j)[2]); } } sort(Array.begin(), Array.end()); src.at<Vec3b>(m, n)[2] = Array[size*size / 2]; } }}//row行，col列//均值滤波:
void meanFilter(Mat& src,int size) {
int row = src.rows, col = src.cols; int start = size / 2; for (int m = start; m < row - start; m++) {for (int n = start; n < col - start; n++) {
int sum = 0; for(int i = -start + m; i <= start + m; i++) { for (int j = -start + n; j <= start + n; j++) { sum = sum + src.at<Vec3b>(i, j)[0]; } } src.at<Vec3b>(m, n)[0] = uchar(sum / size / size); }for (int n = start; n < col - start; n++) {
int sum = 0; for (int i = -start + m; i <= start + m; i++) { for (int j = -start + n; j <= start + n; j++) { sum = sum + src.at<Vec3b>(i, j)[1]; } } src.at<Vec3b>(m, n)[1] = uchar(sum / size / size); }for (int n = start; n < col - start; n++) {
int sum = 0; for (int i = -start + m; i <= start + m; i++) { for (int j = -start + n; j <= start + n; j++) { sum = sum + src.at<Vec3b>(i, j)[2]; } } src.at<Vec3b>(m, n)[2] = uchar(sum / size / size); } }} //膨胀void Open(Mat& src, Mat& img, int size) { int row = src.rows, col = src.cols; int start = size / 2; for (int m = start; m < row - start; m++) {for (int n = start; n < col - start; n++) {
vector<uchar> Array; for (int i = -start + m; i <= start + m; i++) { for (int j = -start + n; j <= start + n; j++) { Array.push_back(src.at<Vec3b>(i, j)[0]); } } sort(Array.begin(), Array.end()); img.at<Vec3b>(m, n)[0] = Array[8]; }for (int n = start; n < col - start; n++) {
vector<uchar> Array; for (int i = -start + m; i <= start + m; i++) { for (int j = -start + n; j <= start + n; j++) { Array.push_back(src.at<Vec3b>(i, j)[1]); } } sort(Array.begin(), Array.end()); img.at<Vec3b>(m, n)[1] = Array[8]; }for (int n = start; n < col - start; n++) {
vector<uchar> Array; for (int i = -start + m; i <= start + m; i++) { for (int j = -start + n; j <= start + n; j++) { Array.push_back(src.at<Vec3b>(i, j)[2]); } } sort(Array.begin(), Array.end()); img.at<Vec3b>(m, n)[2] = Array[8]; } }}/*int Max(vector<uchar> Array1,int size) {
int max = Array1[0]; for (int i = 0; i < 9; i++) { if (Array1[i] > max) max = Array1[i]; } return max;}*/ //腐蚀void Close(Mat& src, Mat& img, int size) { int row = src.rows, col = src.cols; int start = size / 2; for (int m = start; m < row - start; m++) {for (int n = start; n < col - start; n++) {
vector<uchar> Array; for (int i = -start + m; i <= start + m; i++) { for (int j = -start + n; j <= start + n; j++) { Array.push_back(src.at<Vec3b>(i, j)[0]); } } sort(Array.begin(), Array.end()); img.at<Vec3b>(m, n)[0] = Array[0]; }for (int n = start; n < col - start; n++) {
vector<uchar> Array; for (int i = -start + m; i <= start + m; i++) { for (int j = -start + n; j <= start + n; j++) { Array.push_back(src.at<Vec3b>(i, j)[1]); } } sort(Array.begin(), Array.end()); img.at<Vec3b>(m, n)[1] = Array[0]; }for (int n = start; n < col - start; n++) {
vector<uchar> Array; for (int i = -start + m; i <= start + m; i++) { for (int j = -start + n; j <= start + n; j++) { Array.push_back(src.at<Vec3b>(i, j)[2]); } } sort(Array.begin(), Array.end()); img.at<Vec3b>(m, n)[2] = Array[0]; } }}/*int Min(vector<uchar> Array1, int size) {
int min = Array1[0]; for (int i = 0; i < 9; i++) { if (Array1[i] < min) min = Array1[i]; } return min;}*/