zaosheng.rar_加入噪声_噪声

[image,map]=imread('y.jpg'); [m,n]=size(image); figure,imshow(image,map),title('initiative image') I=imnoise(image,'salt & pepper',0.02);%椒盐噪声处理 % I = imnoise(image,'gaussian',0,0.002);%高斯噪声处理 figure,imshow(I,map),title('noised image') %均值滤波 image1=image; H=ones(3)*1/9; I=double(I(:,:,1)); [m,n]=size(I); for i=2:m-1 for j=2:n-1 temp=I(i-1:i+1,j-1:j+1); image1(i,j)=sum(sum(temp.*H)); end end figure,imshow(image1,map),title('均值滤波'); %中值滤波 image2=image; for i=2:m-1 for j=2:n-1 temp=I(i-1:i+1,j-1:j+1); image2(i,j)=median(sort(temp(:))); end end figure,imshow(image2,map),title('中值滤波'); %SNN image3=image; for i=2:m-1 for j=2:n-1 temp1=I(i-1:i+1,j-1:j+1); temp=temp1-I(i,j); if abs(temp(1,1))<abs(temp(3,3)) t1=temp1(1,1); else t1=temp1(3,3); end if abs(temp(1,2))<abs(temp(3,2)) t2=temp1(1,2); else t2=temp1(3,2); end if abs(temp(1,3))<abs(temp(3,1)) t3=temp1(1,3); else t3=temp1(3,1); end if abs(temp(2,1))<abs(temp(2,3)) t4=temp1(1,1); else t4=temp1(3,3); end t=[t1,t2 t3 t4]; image3(i,j)=mean(t); end end figure,imshow(image3,map),title('SNN'); %KNN %Sigma image4=image; for i=3:m-2 for j=3:n-2 temp=I(i-2:i+2,j-2:j+2); sigma=stdd(temp(:)); t1=round(I(i,j)-2*sigma); t2=round(I(i,j)+2*sigma); for ii=1:5 for jj=1:5 if temp(ii,jj)<=t2&temp(ii,jj)>=t1 temp1(ii,jj)=temp(ii,jj); else temp1(ii,jj)=0; end end end mean0=mean(temp1(:)); image4(i,j)=round(mean0); end end figure,imshow(image4,map),title('Sigma');