用MATLAB程序进行图像处理[1]

1、用MATLAB程序进行图像处理一计算图像统计参数：最大值：扫描法：设第一个象素灰度级为最大值，然后与后一个象素灰度级比较，如果后面的大，则把后一象素值赋给最大值，依次逐一比较到图象最后的一个象素，找出最大值。参考程序：A,map=imread(E:lena.bmp); %显示原图imshow(A,map), title(原图);image=double(A);%求负片k=image(1,1);for i=1:256, for j=1:256, if kimage(i,j); k=image(i,j);end, end,end,k%显示负片figure,imshow(rimage,map),ti

2、tle(负片);均值：把图中的所有的象素值累加起来再除以图象的象素的个数。参考程序：A,map=imread(E:lena.bmp); %显示原图imshow(A,map), title(原图);image=double(A);%求负片k=image(1,1);for i=1:256, for j=1:256, if kimage(i,j); k=image(i,j);end, end,end,k%显示负片figure,imshow(rimage,map),title(负片);直方图：把图中的不同灰度等级的象素分别累加起来，再分别除以图象象素的总数。即：p(sk)=nk/n。可以得到原图的灰度

3、值分布图。参考程序：A,map=imread(e:lena.bmp); imshow(A,map), title(原图);image=double(A);for i=1:256, a(i)=0;end,for i=1:256, for j=1:256, b=image(i,j)+1; a(b)=a(b)+1; end,end,for k=1:256, p(k)=a(k)/(2562);end,figure,stem(p);title(直方图);二对比度增强：直方图均衡：原始图的直方图变换为均匀分布的形式，这样就增加了象素灰度值的动态范围从而达到增强对比度的效果。参考程序：A,map=imrea

4、d(e:lena.bmp); imshow(A,map), title(原图);image=double(A);for i=1:256, n(i)=0;end,for i=1:256, for j=1:256, s=image(i,j)+1; n(s)=n(s)+1; end,end,for k=1:256, p(k)=n(k)/(2562);end,figure,bar(p,r);title(直方图);for k=1:256, q(k)=0;end,for k=1:256, for j=1:k, q(k)=q(k)+p(j); end,end,figure,bar(q,y);title(累积

5、直方图);N=256;for k=1:256, o(k)=round(N-1)*q(k)+0.5);end,for i=1:256, for j=1:256, rimage(i,j)=o(image(i,j); endendfigure,imshow(uint8(rimage);title(均衡化后的图);for i=1:256, n(i)=0;end,for i=1:256, for j=1:256, s=rimage(i,j)+1; n(s)=n(s)+1; end,end,for k=1:256, p(k)=n(k)/(2562);end,figure,bar(p,b);title(均衡

6、化的直方图);三图象平滑：中值滤波：中值滤波属于非线性平滑滤波器，它可以消除噪声又能保护图象的细节。参考程序：figure,A,map=imread(e:lena.bmp); %显示原图imshow(A,map), title(原图);image=double(A);u=zeros(1,9);for i=2:255, for j=2:255, u(1)=image(i,j);u(2)=image(i,j+1);u(3)=image(i-1,j+1); u(4)=image(i-1,j);u(5)=image(i-1,j-1);u(6)=image(i,j-1); u(7)=image(i+1,

7、j-1);u(8)=image(i+1,j);u(9)=image(i+1,j+1); for p=1:8, for q=1:8-p, if u(q)u(q+1) k=u(q);u(q)=u(q+1);u(q+1)=k; end, end, end, rimage(i,j)=u(5); end,end, figure,imshow(rimage,map),title(中值滤波);四图象锐化：Sobel算子：是一种空域微分算子，可以通过它锐化图象。参考程序：A,map=imread(e:lena.bmp); image=double(A);u=zeros(1,9);k=zeros(1,9);fo

8、r i=2:255, for j=2:255, u(1)=0*image(i,j);u(2)=2*image(i,j+1);u(3)=1*image(i-1,j+1); u(4)=0*image(i-1,j);u(5)=-1*image(i-1,j-1);u(6)=-2*image(i,j-1); u(7)=-1*image(i+1,j-1);u(8)=0*image(i+1,j);u(9)=1*image(i+1,j+1); rimage1(i,j)=abs(sum(u); k(1)=0*image(i,j);k(2)=0*image(i,j+1);k(3)=1*image(i-1,j+1)

9、; k(4)=2*image(i-1,j);k(5)=1*image(i-1,j-1);k(6)=0*image(i,j-1); k(7)=-1*image(i+1,j-1);k(8)=-2*image(i+1,j);k(9)=-1*image(i+1,j+1); rimage2(i,j)=abs(sum(k); xuhua(i,j)=rimage1(i,j)+rimage2(i,j); end,end, figure,imshow(xuhua,map),title(Sobel锐化);五图象变换： 将图象分块(8*8)，作DCT变换，并作IDCT：DCT是一种可分离图象变换，用来图象压缩编码，

10、IDCT用来解压缩。参考程序：A,map=imread(e:lena.bmp); %显示原图imshow(A,map), title(原图);image=double(A);N=8;for x=1, a(x)=sqrt(1/N);end,for x=2:8, a(x)=sqrt(2/N);end,%dctrimage=zeros(8,8);for x=1:32, for y=1:32, for u=1:N, for v=1:N, for i=1:N, for j=1:N, rimage(i,j)=image(i+(x-1)*8,j+(y-1)*8); b(i,j)=rimage(i,j).*c

11、os(2*(i-1)+1)*(u-1)*pi/(2*N).*cos(2*(j-1)+1)*(v-1)*pi/(2*N); end, end, d(u,v)=sum(sum(b,1),2); C(u,v)=a(u).*a(v).*d(u,v); end,end,xhimagex,y=C;end,end,aa=zeros(8,8);b1=zeros(256,256);for x=1:32, for y=1:32, aa=xhimagex,y; for i=1:8, for j=1:8, b1(i+(x-1)*8,j+(y-1)*8)=aa(i,j); end, end, end,end,figure,imshow(uint8(b1);title(DCT);参考程序：%idctfor x=1:32, for y=1:32, for i=1:N, for j=1:N, C=xhimagex,y; for u=1:N, for v=1:N, h(u,v)=a(u).*a(v).*C(u,v).*cos(2*(i-1)+1)*(u-1)*pi/(2*N).*cos(2*(j-1)+1)*(v-1)*pi/(2*N); end, end, ic(i,j)=sum(sum(h,1),2); end,end,reimagex,y=ic;e