OpenCV-中值滤波

原理：中值滤波的实质就是对滤波窗口大小内的像素点进行排序，然后选择该像素范围内的中值为输出的像素值。中值滤波的主要功能是去除椒盐噪声，类似于黑白电视机的雪花点。

C++：

#include
#include
using namespace std;
using namespace cv;

Mat medianBLUR(const Mat&img, Size winksize, int borderType = BORDER_DEFAULT)
{
	//窗口尺寸
	int H = winksize.height;
	int W = winksize.width;
	//窗口半径
	int h = (H - 1) / 2;
	int w = (W - 1) / 2;
	//图像边界扩充
	Mat expand_image;
	copyMakeBorder(img, expand_image, h, h, w, w, borderType);
	//图像尺寸
	int rows = img.rows;
	int cols = img.cols;
	Mat mediansrc;
	mediansrc.create(rows,cols,CV_8UC1);
	Mat region, re_region, result_region;
	for (int i = 0; i< rows; i++)
	{
		for (int j = 0; j < cols; j++)
		{
			region = expand_image(Rect(j, i, W, H)).clone();
			//将滤波窗口转换为1×1矩阵
			re_region = region.reshape(1, 1);
			//像素排序
			cv::sort(re_region, result_region, SORT_EVERY_ROW);
			uchar number = result_region.at<uchar>(0, ((H*W - 1) / 2));
			mediansrc.at<uchar>(i ,j) = number;
			
		}
	}
	return mediansrc;
};

int main()
{
	Mat src,dst;
	src=imread("D:/testimage/dog1.jpg");
	cvtColor(src, src, COLOR_BGR2GRAY);
	dst = medianBLUR(src, Size(7, 7),  BORDER_DEFAULT);
	imshow("original image", src);
	imshow("median image", dst);
	waitKey(0);
	return 0;
};

Python：

import cv2 as cv
import numpy as np
import random

    #椒盐噪声图像
def addsalt(dst,number):
    rows,cols=dst.shape[:2]
    saltdst=np.copy(dst)
    for i in range(number):
        m = random.randint(0,rows-1)
        n = random.randint(0, cols - 1)
        saltdst[m][n]=255
    return saltdst

def median_blur(img,ksize):
    rows,cols=img.shape
    #窗口半径
    h = (ksize[0] - 1) // 2
    w = (ksize[1] - 1) // 2
    #创建中值滤波空白图像
    medianblur_image=np.zeros(img.shape,img.dtype)
    #扩充图像边界
    expand_image=cv.copyMakeBorder(img,h,h,w,w,borderType=cv.BORDER_DEFAULT)
    for i in range(rows):
        for j in range(cols):
            region=expand_image[i:i+h,j:j+w]
            medianblur_image[i][j]=np.median(region)
            j+=1
        i+=1
    return medianblur_image


if __name__=="__main__":
    img=cv.imread("D:/testimage/dog0.jpg")
    dst=addsalt(img,1000)
    gray_dst=cv.cvtColor(dst,cv.COLOR_BGR2GRAY)
    cv.imshow("original image",gray_dst)
    #7×7的中值滤波窗口
    src=median_blur(gray_dst,(7,7))
    cv.imshow("medianblur_src",src)
    cv.waitKey(0)
    cv.destroyAllWindows()

结果：