watershed.zip_watershed_聚类道路_道路 提取_道路分割_道路提取

I=imread('houhu.png'); figure(1); imshow(I);title('原始图像'); C = makecform('srgb2lab'); %设置转换格式,lab——l为亮度，a为颜色，b为颜色，l取0至100（纯黑—纯白），a表示从红色到绿色的范围，b表示从黄色到蓝色 J = applycform(I,C); %进行K-mean聚类将图像分割成6个区域 ab = double(J(:,:,2:3)); %取出lab空间的a分量和b分量 nrows = size(ab,1); ncols = size(ab,2); ab = reshape(ab,nrows*ncols,2); nColors = 6; %分割的区域个数为6 [cluster_idx cluster_center] = kmeans(ab,nColors,'distance','sqEuclidean','Replicates',2); %重复聚类2次 pixel_labels1 = reshape(cluster_idx==1,nrows,ncols); figure(); imshow(pixel_labels1,[]), title('聚类结果1'); pixel_labels2 = reshape(cluster_idx==2,nrows,ncols); figure(); imshow(pixel_labels2,[]), title('聚类结果2'); pixel_labels3 = reshape(cluster_idx==3,nrows,ncols); figure(); imshow(pixel_labels3,[]), title('聚类结果3'); pixel_labels4 = reshape(cluster_idx==4,nrows,ncols); figure(); imshow(pixel_labels4,[]), title('聚类结果4'); pixel_labels5 = reshape(cluster_idx==5,nrows,ncols); figure(); imshow(pixel_labels5,[]), title('聚类结果5'); pixel_labels6 = reshape(cluster_idx==6,nrows,ncols); figure(); imshow(pixel_labels6,[]), title('聚类结果6'); [m n]=size(I); [i j]=size(pixel_labels3); size = [593 740]; J1 = imresize(I,size); pixel_labels3 = imresize(pixel_labels3,size); J2=imadd(double(rgb2gray(J1)),double(pixel_labels3),'uint8'); imshow(J2);title('匹配图像'); W=watershed(pixel_labels3); imshow(W);title('道路提取图像');