zhongzhilvbo.zip_matlab_中值滤波

function main() close all;clear all; % p=imread('rice.png'); % 输入待处理的图像，使用matlab里有的一个图像 p1=imnoise(p,'salt & pepper',0.1); % 加入椒盐噪声 [m,n]=size(p1); block_size=9; k=floor(block_size/2); % block_size 为3x3,5x5,9x9…… p2=zeros(m+2*k,n+2*k); p2(k+1:m+k,k+1:n+k)=p; % 原始图像放中间 p2(1:k,1:k)=p(1,1); % 扩展左上、左下、右上、右下 p2(1:k,n+k+1:n+2*k)=p(1,n); p2(m+k+1:m+2*k,n+k+1:n+2*k)=p(m,n); p2(m+k+1:m+2*k,1:k)=p(m,1); for i = 1:k % 扩展上下左右 p2(i,k+1:n+k)=p(1,1:n); p2(k+1:m+k,n+k+i)=p(1:m,n); p2(m+k+i,k+1:n+k)=p(m,1:n); p2(k+1:m+k,i)=p(1:m,1); end; p3=zeros(m,n); % 构建输出图像的矩阵 pixel_block=zeros(1,block_size^2); for i = 1:m for j = 1:n k=floor(block_size/2); pixel_block=reshape(p2(i:i+2*k,j:j+2*k),block_size^2,1); % 转换矩阵 sorted_block=sort(pixel_block); % 排序 median_position=ceil(block_size^2/2); % 寻找中值的位置 block_median=sorted_block(median_position); p3(i,j)=block_median; end; end; p3=uint8(p3); figure subplot(2,2,1),imshow(p); subplot(2,2,2),imshow(p1); subplot(2,2,3),imshow(p3); [PSNR, MSE] = psnr(p,p3) % 图像峰值信噪比PSNR、均方根误差MSE % By lyqmath % Dalian University of Technology % School of Mathematical Sciences function [PSNR, MSE] = psnr(X, Y) % 计算峰值信噪比PSNR、均方根误差MSE % 如果输入Y为空，则视为X与其本身来计算PSNR、MSE if nargin<2 D = X; else if any(size(X)~=size(Y)) error('The input size is not equal to each other!'); end D = X-Y; end MSE = sum(D(:).*D(:))/prod(size(X)); PSNR = 10*log10(255^2/MSE);