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1、matlab图像分割算法源码1. 图像反转MATLAB程序实现如下：l=imread('xian.bmp');J=double(l);J=-J+(256-1);%图像反转线性变换H=uint8(J);subplot(1,2,1),imshow(l);subplot(1,2,2),imshow(H);2. 灰度线性变换MATLAB程序实现如下：I=imread('xian.bmp');subplot(2,2,1),imshow(I);title('原始图像');axis(50,250,50,200);axis on;%显示坐标系l1=rgb2gra
2、y(I);subplot(2,2,2),imshow(I1);title('灰度图像');axis(50,250,50,200);axis on;%显示坐标系J=imadjust(l1,0.1 0.5,); %局部拉伸，把0.1 0.5内的灰度拉伸为0 1subplot(2,2,3),imshow(J);title('线性变换图像0.1 0.5');axis(50,250,50,200);grid on;%显示网格线axis on;%显示坐标系K=imadjust(I1,0.3 0.7,); % 局部拉伸，把0.3 0.7内的灰度拉伸为0 1 subplot(2
3、,2,4),imshow(K);title('线性变换图像0.3 0.7');axis(50,250,50,200);grid on;%显示网格线axis on;%显示坐标系3. 非线性变换MATLAB程序实现如下： l=imread('xian.bmp');I仁rgb2gray(l); subplot(1,2,1),imshow(l1);title('灰度图像');axis(50,250,50,200);grid on;%显示网格线axis on;%显示坐标系J=double (I1);J=40*(log(J+1);H=uint8(J);sub
4、plot(1,2,2),imshow(H);title('对数变换图像');axis(50,250,50,200);grid on;%显示网格线axis on;%显示坐标系4. 直方图均衡化MATLAB程序实现如下：I=imread('xian.bmp');I=rgb2gray(I);figure;subplot(2,2,1);imshow(I);subplot(2,2,2);imhist(I);I1=histeq(I);figure;subplot(2,2,1);imshow(I1);subplot(2,2,2);imhist(I1);5. 线性平滑滤波器用M
5、ATLAB实现领域平均法抑制噪声程序:I=imread('xian.bmp');subplot(231) imshow(l) title（'原始图像'）I=rgb2gray(l);I1=imnoise(l,'salt & pepper',0.02);subplot(232) imshow(I1) title（'添加椒盐噪声的图像'）k1=filter2(fspecial('average',3),l1)/255;%进行3*3模板平滑滤波k2=filter2(fspecial('average'
6、;,5),I1)/255;%进行5*5模板平滑滤波k3=filter2(fspecial('average',7),I1)/255;%进行7*7模板平滑滤波k4=filter2(fspecial('average',9),l1)/255;%进行9*9模板平滑滤波subplot(233),imshow(k1);title('3*3模板平滑滤波');subplot(234),imshow(k2);title('5*5模板平滑滤波');subplot(235),imshow(k3);title('7*7模板平滑滤波');
7、subplot(236),imshow(k4);title('9*9模板平滑滤波');k1=medfilt2(J);%进行3*3模板中值滤波k2=medfilt2(J,5,5);%进行5*5模板中值滤波k3=medfilt2(J,7,7);%进行7*7模板中值滤波k4=medfilt2(J,9,9);%进行9*9模板中值滤波subplot(233),imshow(k1);title('3*3模板中值滤波');subplot(234),imshow(k2);title('5*5模板中值滤波');subplot(235),imshow(k3);tit
8、le('7*7模板中值滤波');subplot(236),imshow(k4);title('9*9模板中值滤波');6中值滤波器用MATLAB实现中值滤波程序如下:l=imread('xian.bmp');I=rgb2gray(l);J=imnoise(l,'salt&pepper',0.02);subplot(231),imshow(l);title('原图像');');subplot(232),imshow(J);title('添加椒盐噪声图像用Sobel算子和拉普拉斯对图像锐化:su
9、bplot(2,2,1),imshow(l);title('原始图像');axis(50,250,50,200);grid on;%显示网格线axis on;%显示坐标系I1=im2bw(I);subplot(2,2,2),imshow(I1);title('二值图像');axis(50,250,50,200);grid on;%显示网格线axis on;%显示坐标系H=fspecial('sobel');%选择 sobel 算子J=filter2(H,l1);% 卷积运算subplot(2,2,3),imshow(J);title('s
10、obel算子锐化图像');axis(50,250,50,200);grid on;%显示网格线axis on;%显示坐标系h=0 1 0,1 -4 1,0 1 0;%拉普拉斯算子J1=conv2(l1,h,'same');% 卷积运算subplot(2,2,4),imshow(J1);title('拉普拉斯算子锐化图像)；axis(50,250,50,200);grid on;%显示网格线axis on;%显示坐标系7. 梯度算子检测边缘用MATLAB实现如下：I=imread('xian.bmp');subplot(2,3,1);imshow(
11、I);title('原始图像');axis(50,250,50,200);grid on;%显示网格线axis on;%显示坐标系I1=im2bw(I);subplot(2,3,2);imshow(ll);title('二值图像');axis(50,250,50,200);grid on;%显示网格线axis on;%显示坐标系I2=edge(l1,'roberts');figure;subplot(2,3,3);imshow(I2);title('roberts算子分割结果');axis(50,250,50,200);grid
12、on;%显示网格线axis on;%显示坐标系I3=edge(I1,'sobel');subplot(2,3,4);imshow(I3);title('sobel算子分割结果');axis(50,250,50,200);grid on;%显示网格线axis on;%显示坐标系l4=edge(l1,'Prewitt');subplot(2,3,5);imshow(I4);title('Prewitt算子分割结果');axis(50,250,50,200);grid on;%显示网格线axis on;%显示坐标系8. LOG算子检测边
13、缘用MATLAB程序实现如下：I=imread('xian.bmp');subplot(2,2,1);imshow(I);title('原始图像');I1=rgb2gray(I);subplot(2,2,2);imshow(ll);title('灰度图像');I2=edge(l1,'log');subplot(2,2,3);imshow(I2);title('log算子分割结果');9. Canny算子检测边缘用MATLAB程序实现如下：l=imread('xian.bmp');subplot(2,
14、2,1);imshow(I);title('原始图像')I1=rgb2gray(I);subplot(2,2,2);imshow(I1);title('灰度图像');I2=edge(I1,'canny');subplot(2,2,3);imshow(I2);title('canny算子分割结果');10. 边界跟踪(bwtraceboundary 函数)clcclear allI=imread('xian.bmp');figureimshow(I);title('原始图像');I1=rgb2gray
15、(I);%将彩色图像转化灰度图像threshold=graythresh(I1);%计算将灰度图像转化为二值图像所需的门限BW=im2bw(I1, threshold);%将灰度图像转化为二值图像figureimshow(BW);title('二值图像');dim=size(BW);col=round(dim(2)/2)-90;%计算起始点列坐标row=find(BW(:,col),1);%计算起始点行坐标connectivity=8;num_points=180; contour=bwtraceboundary(BW,row,col,'N',connectiv
16、ity,num_points);%提取边界figureimshow(l1);hold on;plot(contour(:,2),contour(:,1), 'g','LineWidth' ,2);title('边界跟踪图像');11. Hough 变换I= imread('xian.bmp');rotI=rgb2gray(I);subplot(2,2,1);imshow(rotI);title('灰度图像');axis(50,250,50,200);grid on;axis on;BW=edge(rotl,'
17、;prewitt');subplot(2,2,2);imshow(BW);title('prewitt算子边缘检测后图像)；axis(50,250,50,200);grid on;axis on;H,T,R=hough(BW);subplot(2,2,3);imshow(H,'XData',T,'YData',R,'lnitialMagnification','fit');title('霍夫变换图');xlabel('theta'),ylabel('rho');axi
18、s on , axis normal, hold on;P=houghpeaks(H,5,'threshold',ceil(0.3*max(H(:);x=T(P(:,2);y=R(P(:,1);plot(x,y,'s','color','white');lines=houghlines(BW,T,R,P,'FillGap',5,'MinLength',7);subplot(2,2,4);,imshow(rotl);title('霍夫变换图像检测)；axis(50,250,50,200);gr
19、id on;axis on;hold on;max_len=0;for k=1:length(lines)xy=lines(k).point1;lines(k).point2;plot(xy(:,1),xy(:,2),'LineWidth',2,'Color','green');plot(xy(1,1),xy(1,2),'x','LineWidth',2,'Color','yellow');plot(xy(2,1),xy(2,2),'x','LineWidth
20、',2,'Color','red');Ien=norm(lines(k).point1-lines(k).point2);if(len>max_len)max_len=len;xy_long=xy;endendplot(xy_long(:,1),xy_long(:,2),'LineWidth',2,'Color','cyan');12. 直方图阈值法用MATLAB实现直方图阈值法：I=imread('xian.bmp');I1=rgb2gray(I);figure;subplot(2,
21、2,1);imshow(I1);title('灰度图像')axis(50,250,50,200);grid on;%显示网格线axis on;%显示坐标系m,n=size(I1);%测量图像尺寸参数GP=zeros(1,256);%预创建存放灰度岀现概率的向量for k=0:255GP(k+1)=length(find(l1=k)/(m*n);%计算每级灰度出现的概率，将其存入GP中相应位置endsubplot(2,2,2),bar(0:255,GP,'g')% 绘制直方图title('灰度直方图')xlabel('灰度值')yl
22、abel('出现概率')I2=im2bw(I,150/255);subplot(2,2,3),imshow(l2);title('阈值150的分割图像')axis(50,250,50,200);grid on;%显示网格线axis on;%显示坐标系I3=im2bw(I,200/255);%subplot(2,2,4),imshow(l3);title('阈值200的分割图像')axis(50,250,50,200);grid on;%显示网格线axis on;%显示坐标系13. 自动阈值法：Otsu法用MATLAB实现Otsu算法：clccle
23、ar allI=imread('xian.bmp');subplot(1,2,1),imshow(I);title('原始图像')axis(50,250,50,200);grid on;%显示网格线axis on;%显示坐标系level=graythresh(l); % 确定灰度阈值BW=im2bw(l,level);subplot(1,2,2),imshow(BW);title('Otsu法阈值分割图像')axis(50,250,50,200);grid on;axis on;%显示网格线%显示坐标系15.膨胀操作l=imread('x
24、ian.bmp');%载入图像1仁 rgb2gray(l);subplot(1,2,1);imshow(l1);title（'灰度图像'）axis(50,250,50,200);grid on;%显示网格线axis on;%显示坐标系se=strel('disk',1);%生成圆形结构元素I2=imdilate(I1,se);%用生成的结构元素对图像进行膨胀subplot(1,2,2);imshow(I2);title（'膨胀后图像'）;axis(50,250,50,200);grid on;%显示网格线axis on;%显示坐标系16.
25、腐蚀操作MATLAB实现腐蚀操作I=imread('xian.bmp');%载入图像I1=rgb2gray(I);subplot(1,2,1);imshow(I1);title（'灰度图像'）axis(50,250,50,200);grid on;%显示网格线axis on;%显示坐标系se=strel('disk',1);%生成圆形结构元素I2=imerode(I1,se);%用生成的结构元素对图像进行腐蚀subplot(1,2,2);imshow(I2);title（'腐蚀后图像'）;axis(50,250,50,200);g
26、rid on;%显示网格线axis on;%显示坐标系axis on;%显示坐标系axis on;%显示坐标系17. 开启和闭合操作用MATLAB实现开启和闭合操作l=imread('xian.bmp');%载入图像axis on;%显示坐标系axis on;%显示坐标系subplot(2,2,1),imshow(l);axis(50,250,50,200);axis on;%显示坐标系axis on;%显示坐标系axis on;%显示坐标系I1=rgb2gray(I);subplot(2,2,2),imshow(I1);title（'灰度图像'）;axis(5
27、0,250,50,200);axis on;%显示坐标系se=strel('disk',1);%采用半径为1的圆作为结构元素I2=imopen(I1,se);%开启操作I3=imclose(l1,se);%闭合操作axis on;%显示坐标系axis on;%显示坐标系subplot(2,2,3),imshow(l2);title（'开启运算后图像'）;axis(50,250,50,200);axis on;%显示坐标系axis on;%显示坐标系axis on;%显示坐标系subplot(2,2,4),imshow(l3);title（'闭合运算后图像
28、'）;axis(50,250,50,200);axis on;%显示坐标系axis on;%显示坐标系axis on;%显示坐标系18. 开启和闭合组合操作l=imread('xian.bmp');%载入图像axis on;%显示坐标系axis on;%显示坐标系subplot(3,2,1),imshow(l);title（'原始图像'）;axis(50,250,50,200);I1=rgb2gray(l);axis on;%显示坐标系title('灰度图像');axis(50,250,50,200);axis on;%显示坐标系se=s
29、trel('disk',1);I2=imopen(l1,se);% 开启操作I3=imclose(l1,se);%闭合操作subplot(3,2,3),imshow(l2);title('开启运算后图像');axis(50,250,50,200);axis on;%显示坐标系subplot(3,2,4),imshow(l3);title('闭合运算后图像');axis(50,250,50,200);axis on;%显示坐标系se=strel('disk',1);I4=imopen(I1,se);I5=imclose(I4,se)
30、;subplot(3,2,5),imshow(I5);%开一闭运算图像title('开一闭运算图像');axis(50,250,50,200);axis on;%显示坐标系I6=imclose(I1,se);I7=imopen(l6,se);subplot(3,2,6),imshow(l7);% 闭一开运算图像title('闭一开运算图像');axis(50,250,50,200);axis on;%显示坐标系19. 形态学边界提取利用MATLAB实现如下：l=imread('xian.bmp');% 载入图像subplot(1,3,1),ims
31、how(l);title('原始图像');axis(50,250,50,200);grid on;%显示网格线axis on;%显示坐标系I仁im2bw(l);subplot(1,3,2),imshow(l1);title('二值化图像');axis(50,250,50,200);grid on;%显示网格线axis on;%显示坐标系I2=bwperim(I1);%获取区域的周长subplot(1,3,3),imshow(I2);title('边界周长的二值图像');axis(50,250,50,200);grid on;axis on;20.
32、 形态学骨架提取利用MATLAB实现如下：l=imread('xian.bmp');subplot(2,2,1),imshow(I);title('原始图像');axis(50,250,50,200);axis on;I1=im2bw(I);subplot(2,2,2),imshow(I1);title('二值图像');axis(50,250,50,200);axis on;I2=bwmorph(I1,'skel',1);subplot(2,2,3),imshow(I2);title('1次骨架提取');axis(50,250,50,200);axis on;I3=bwmorph(I1,'skel',2);subplot(2,2,4),imshow(I3);title('2次骨架提取');axis(50,250,50,200);axis on;21. 直接提取四个顶点坐标I = imread('xian.bmp');I = K：,：,1)；BW=im2bw(l);figureimshow(BW)x,y=getpts