noise.zip_NOISE_去噪_去噪matlab_噪声_图片去噪平台

clc;close all;clear; %对图像做预处理 source=imread('source.jpg'); source = rgb2gray(source); source=imresize(source,[256,256]); figure; imshow(source); %生成噪声图 noise1 = imnoise(source,'salt & pepper', 0.1); %椒盐噪声 noise2 = imnoise(source,'gaussian'); %高斯噪声 noise3 = imnoise(source,'speckle'); %斑点噪声 figure; subplot(3,5,1); imshow(noise1); subplot(3,5,6); imshow(noise2); subplot(3,5,11); imshow(noise3); %用中值滤波法进行滤波 res1=medfilt2(noise1); subplot(3,5,2); imshow(res1); res2=medfilt2(noise2); subplot(3,5,7); imshow(res2); res3=medfilt2(noise3); subplot(3,5,12); imshow(res3); %用均值滤波法进行滤波 F=fspecial('average',3); %生成滤波器 res1=filter2(F,noise1)/255; %用生成的滤波器进行滤波,并归一化 subplot(3,5,3); imshow(res1); res2=filter2(F,noise2)/255; %用生成的滤波器进行滤波,并归一化 subplot(3,5,8); imshow(res2); res3=filter2(F,noise3)/255; %用生成的滤波器进行滤波,并归一化 subplot(3,5,13); imshow(res3); %用高斯滤波法进行滤波 sigma=1.2; %标准差大小 window=double(uint8(3*sigma)*2+1); H=fspecial('gaussian', window, sigma); %产生滤波模板 res1=imfilter(noise1,H,'replicate'); subplot(3,5,4); imshow(res1); res2=imfilter(noise2,H,'replicate'); subplot(3,5,9); imshow(res2); res3=imfilter(noise3,H,'replicate'); subplot(3,5,14); imshow(res3); %使用自适应中值滤波法 res1=IAMF(noise1); subplot(3,5,5); imshow(res1); res2=IAMF(noise2); subplot(3,5,10); imshow(res2); res3=IAMF(noise3); subplot(3,5,15); imshow(res3); function res=IAMF(img) done = false(size(img)); temp=img; temp(:)=0; top=7; for k = 3:2:top min = ordfilt2(img, 1, ones(k, k), 'symmetric'); max = ordfilt2(img, k * k, ones(k, k), 'symmetric'); med = medfilt2(img, [k k], 'symmetric'); level = (med > min) & (max > med) & ... ~done; z = (img > min) & (max > img); outputZxy = level & z; outputZmed = level & ~z; temp(outputZxy) = img(outputZxy); temp(outputZmed) = med(outputZmed); done = done | level; if all(done(:)) break; end end temp(~done) = med(~done); res=temp; end