圖像噪聲的抑制(18103317)

1、實驗內容專業(yè)：電子信息工程學號：18103317實驗要求：1、 掌握以上噪聲抑制的基本算法。2、 讀出圖像rice.png，分別加椒鹽噪聲和高斯噪聲，得到兩幅帶有噪聲的圖像。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、 分別兩幅圖像進行均值濾波（使用）和中值濾波，比較實驗結果。一對有高斯噪聲圖像進行濾波(1) 對有高斯噪聲的圖像進行均值濾波：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(濾波之前(加高斯噪聲);figure,imshow(uint8(b);title(采用均值

3、濾波后);(2) 對有高斯噪聲的圖像進行中值濾波：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(中值濾波之前);figure,imshow(uint8(f);title(中值濾波之后);二對有椒鹽噪聲圖像進行濾波(1) 對有椒鹽噪聲的圖像進行均值濾波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(濾波之前(加高斯噪聲);figure,imshow(uint8(b);title(采用均值濾波后);(2) 對有椒鹽噪聲的圖像進行種植濾波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