边缘检测9种方法

clear im_sourse=imread('../data/fruit.jpg');%数据获取 figure subplot(2,2,1); imshow(im_sourse); title('sourse image'); %imshow(im_sourse); [row,col,z]=size(im_sourse); R=rand(row,col); D=R>0.1; D=double(D); im_sourse=double(im_sourse); for i=1:3 im_new(:,:,i)=D.*im_sourse(:,:,i); end im_show=uint8(im_new); im_a=rgb2gray(im_show); subplot(2,2,2); imshow(im_show); title('noise image'); a=4; %定义滤波窗口大小 b=(a+1)/2; c=a^2/2; %选取中值 b=ceil(b); c=ceil(c); temp=zeros(a^2,1); %准备序列 W=zeros(a,a); %滤波窗口 im=double(im_a); W=double(W); for i=1:a for j=1:a W(i,j)=1; %窗口赋初值 end end for z=1:3 for x=b:(row-b) for y=b:(col-b) i=1; for s=1:a for t=1:a temp(i)=W(s,t)*im_new(x+s-b+1,y+t-b+1,z);%选取周围数据 i=i+1; end end temp=sort(temp); im_newcolor(x,y,z)=temp(c); %获取中间值生成新的图形 end end end im=uint8(im); im_newcolor=uint8(im_newcolor); subplot(2,2,3) imshow(im); title('noise gray image'); subplot(2,2,4) imshow(im_newcolor); title('managed color image'); W %在command window显示滤波模版 size(im_newcolor)