自定义中值滤波函数

#include "opencv2/imgproc.hpp"

#include "opencv2/highgui.hpp"

#include

using namespace cv;

using namespace std;

//求九个数的中值

uchar Median(uchar n1, uchar n2, uchar n3, uchar n4, uchar n5,

	uchar n6, uchar n7, uchar n8, uchar n9) {

	uchar arr[9];

	arr[0] = n1;

	arr[1] = n2;

	arr[2] = n3;

	arr[3] = n4;

	arr[4] = n5;

	arr[5] = n6;

	arr[6] = n7;

	arr[7] = n8;

	arr[8] = n9;

	for (int gap = 9 / 2; gap > 0; gap /= 2)//希尔排序

		for (int i = gap; i < 9; ++i)

			for (int j = i - gap; j >= 0 && arr[j] > arr[j + gap]; j -= gap)

				swap(arr[j], arr[j + gap]);

	return arr[4];//返回中值

}



//图像椒盐化

void salt(Mat &image, int num) {

	if (!image.data) return;//防止传入空图

	int i, j;

	srand(time(NULL));

	for (int x = 0; x < num; ++x) {

		i = rand() % image.rows;

		j = rand() % image.cols;

		image.at(i, j)[0] = 255;

		image.at(i, j)[1] = 255;

		image.at(i, j)[2] = 255;

	}

}



//中值滤波函数
void MedianFlitering(const Mat &src, Mat &dst) {
	if (!src.data)return;
	//创建目标矩阵
	Mat _dst(src.size(), src.type());
	for (int i = 0; i < src.rows; ++i)
		for (int j = 0; j < src.cols; ++j) {
			if ((i - 1) > 0 && (i + 1) < src.rows && (j - 1) > 0 && (j + 1) < src.cols) {
				_dst.at(i, j)[0] = Median(src.at(i, j)[0], src.at(i + 1, j + 1)[0],
					src.at(i + 1, j)[0], src.at(i, j + 1)[0], src.at(i + 1, j - 1)[0],
					src.at(i - 1, j + 1)[0], src.at(i - 1, j)[0], src.at(i, j - 1)[0],
					src.at(i - 1, j - 1)[0]);
				_dst.at(i, j)[1] = Median(src.at(i, j)[1], src.at(i + 1, j + 1)[1],
					src.at(i + 1, j)[1], src.at(i, j + 1)[1], src.at(i + 1, j - 1)[1],
					src.at(i - 1, j + 1)[1], src.at(i - 1, j)[1], src.at(i, j - 1)[1],
					src.at(i - 1, j - 1)[1]);
				_dst.at(i, j)[2] = Median(src.at(i, j)[2], src.at(i + 1, j + 1)[2],
					src.at(i + 1, j)[2], src.at(i, j + 1)[2], src.at(i + 1, j - 1)[2],
					src.at(i - 1, j + 1)[2], src.at(i - 1, j)[2], src.at(i, j - 1)[2],
					src.at(i - 1, j - 1)[2]);
			}
			else
				_dst.at(i, j) = src.at(i, j);
		}
	_dst.copyTo(dst);//拷贝
}





void main() {

	Mat image = imread("F:/2.png");

	Mat Salt_Image;

	image.copyTo(Salt_Image);

	salt(Salt_Image, 3000);

	Mat image3, image4;

	MedianFlitering(Salt_Image, image3);

	medianBlur(Salt_Image, image4, 3);

	imshow("图片椒盐化处理后", Salt_Image);

	imshow("自定义中值滤波处理后", image3);

	imshow("openCV自带的中值滤波", image4);

	waitKey();

}