图像噪声的抑制(18103317)

1、实验内容专业：电子信息工程学号：18103317实验要求：1、 掌握以上噪声抑制的基本算法。2、 读出图像rice.png，分别加椒盐噪声和高斯噪声，得到两幅带有噪声的图像。I=imread(rice.png);figure,imshow(I);J1=imnoise(I,gaussian,0,0.02);figure,imshow(J1);J2=imnoise(I,salt & pepper,0.05);figure,imshow(J2);3、 分别两幅图像进行均值滤波（使用）和中值滤波，比较实验结果。一对有高斯噪声图像进行滤波(1) 对有高斯噪声的图像进行均值滤波：I=imread(rice

2、.png);J1=imnoise(I,gaussian,0,0.02);K=double(J1);m n=size(K);b=K;for x=2:m-1 for y=2:n-1 s=0; Xin=K(x-1,y-1),K(x,y-1),K(x+1,y-1),K(x-1,y),K(x,y), K(x+1,y),K(x-1,y+1),K(x,y+1),K(x+1,y+1); for z=1:9 s=s+xin(z); end b(x,y)=s/9; endendfigure,imshow(J1);title(滤波之前(加高斯噪声);figure,imshow(uint8(b);title(采用均值

3、滤波后);(2) 对有高斯噪声的图像进行中值滤波：clear,clc;I=imread(rice.png);J1=imnoise(I,gaussian,0,0.02);K=double(J1);m n=size(K);f=K;for x=2:m-1 for y=2:n-1 a = 0; a =K(x-1,y-1),K(x,y-1),K(x+1,y-1),K(x-1,y),K(x,y),K(x+1,y),K(x-1,y+1),K(x,y+1),K(x+1,y+1); b=0; c=0; for z=1:8; b=a(z); c=z; for zz=z+1:9 if a(zz)b b=a(zz);

4、 c=zz; end end a(c)=a(z); a(z)=b; end f(x,y)=a(5); endendfigure,imshow(J1);title(中值滤波之前);figure,imshow(uint8(f);title(中值滤波之后);二对有椒盐噪声图像进行滤波(1) 对有椒盐噪声的图像进行均值滤波I=imread(rice.png);J1=imnoise(I,salt & pepper,0.02);K=double(J1);m n=size(K);b=K;for x=2:m-1 for y=2:n-1 s=0; xin=K(x-1,y-1),K(x,y-1),K(x+1,y-

5、1),K(x-1,y),K(x,y),K(x+1,y),K(x-1,y+1),K(x,y+1),K(x+1,y+1); for z=1:9 s=s+xin(z); end b(x,y)=s/9; endendfigure,imshow(J1);title(滤波之前(加高斯噪声);figure,imshow(uint8(b);title(采用均值滤波后);(2) 对有椒盐噪声的图像进行种植滤波I=imread(rice.png);J1=imnoise(I,salt & pepper,0.02);K=double(J1);m n=size(K);f=K;for x=2:m-1 for y=2:n-1 a = 0; a =K(x-1,y-1),K(x,y-1),K(x+1,y-1),K(x-1,y),K(x,y),K(x+1,y),K(x-1,y+1),K(x,y+1),K(x+1,y+1); b=0; c=0; for z=1:8; b=a(z); c=z; for zz=z+1:9 if a(zz)b b=a(zz); c=zz; end end a(c)=a(z); a(z)=b; end