【谷速软件】matlab源码-实用源代码

1、1.图像反转MATLAB 程序实现如下：I=imread('xian.bmp');J=double(I);J=-J+(256-1);                 %图像反转线性变换H=uint8(J);subplot(1,2,1),imshow(I);subplot(1,2,2),imshow(H);2.灰度线性变换MATLAB 程序实现如下：I=imread('xian.bmp');sub

2、plot(2,2,1),imshow(I);title('原始图像');axis(50,250,50,200);axis on;                  %显示坐标系I1=rgb2gray(I);subplot(2,2,2),imshow(I1);title('灰度图像');axis(50,250,50,200);axis on;    

3、;              %显示坐标系J=imadjust(I1,0.1 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;            

4、0;     %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 1subplot(2,2,4),imshow(K);title('线性变换图像0.3 0.7');axis(50,250,50,200);grid on; &

5、#160;                %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：I=imread('xian.bmp');I1=rgb2gray(I);subplo

6、t(1,2,1),imshow(I1);title(' 灰度图像');axis(50,250,50,200);grid on;                  %显示网格线axis on;                  

7、;%显示坐标系J=double(I1);J=40*(log(J+1);H=uint8(J);subplot(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;         

8、         %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MATLAB实现领域平均法抑制噪声程序：I=imread('x

9、ian.bmp');subplot(231)imshow(I)title('原始图像')I=rgb2gray(I);I1=imnoise(I,'salt & pepper',0.02);subplot(232)imshow(I1)title(' 添加椒盐噪声的图像')k1=filter2(fspecial('average',3),I1)/255;          %进行3*3模板平滑滤波k2=filter2(fs

10、pecial('average',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),I1)/255;   

11、0;      %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');subplot(236),imshow(k4);title('9*9 模板平滑滤波');6.中值滤波器用MATLAB实现中值滤波程序如下：I=imread('xia

12、n.bmp');I=rgb2gray(I);J=imnoise(I,'salt&pepper',0.02);subplot(231),imshow(I);title('原图像');subplot(232),imshow(J);title('添加椒盐噪声图像');k1=medfilt2(J);            %进行3*3模板中值滤波k2=medfilt2(J,5,5);   &

13、#160;  %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);title('

14、;7*7模 板中值滤波');subplot(236),imshow(k4);title('9*9 模板中值滤波');7.用Sobel算子和拉普拉斯对图像锐化：I=imread('xian.bmp');subplot(2,2,1),imshow(I);title('原始图像');axis(50,250,50,200);grid on;                 

15、60;%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;             

16、60;    %显示网格线axis on;                  %显示坐标系H=fspecial('sobel');     %选择sobel算子J=filter2(H,I1);          &

17、#160; %卷积运算subplot(2,2,3),imshow(J);title('sobel算子锐化图像');axis(50,250,50,200);grid on;                  %显示网格线axis on;             &#

18、160;    %显示坐标系h=0 1 0,1 -4 1,0 1 0;   %拉普拉斯算子J1=conv2(I1,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;     &

19、#160;            %显示网格线axis on;                  %显示坐标系8.梯度算子检测边缘用 MATLAB实现如下：I=imread('xian.bmp');subplot(2,3,1);imshow(I);title('原始图像

20、9;);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);imsho

21、w(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I2=edge(

22、I1,'roberts');figure;subplot(2,3,3);imshow(I2);title('roberts算子分割结果');axis(50,250,50,200);grid on;                  %显示网格线axis on;          

23、0;       %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;   

24、;               %显示坐标系I4=edge(I1,'Prewitt');subplot(2,3,5);imshow(I4);title('Prewitt算子分割结果 ');axis(50,250,50,200);grid on;              

25、60;   %显示网格线axis on;                  %显示坐标系9.LOG算子检测边缘用 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(I1);title(&#

26、39;灰度图像');I2=edge(I1,'log');subplot(2,2,3);imshow(I2);title('log算子分割结果');10.Canny算子检测边 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(I1);title('灰度图像');I2=edge(I1,'canny');subplot(2,2,

27、3);imshow(I2);title('canny算子分割结果');11.边界跟踪 （bwtraceboundary函数）clcclear allI=imread('xian.bmp');figureimshow(I);title('原始图像');I1=rgb2gray(I);                %将彩色图像转化灰度图像threshold=graythresh(I1);

28、60;       %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)

29、,1);          %计算起始点行坐标connectivity=8;num_points=180;contour=bwtraceboundary(BW,row,col,'N',connectivity,num_points);%提取边界figureimshow(I1);hold on;plot(contour(:,2),contour(:,1), 'g','LineWidth' ,2);title('边界跟踪图像');12.

30、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(rotI,'prewitt');subplot(2,2,2);imshow(BW);title(

31、'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,'InitialMagnification','fit');title('霍夫变换图&

32、#39;);xlabel('theta'),ylabel('rho');axis 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);,i

33、mshow(rotI);title('霍夫变换图像检测');axis(50,250,50,200);grid 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

34、9;,'green');plot(xy(1,1),xy(1,2),'x','LineWidth',2,'Color','yellow');plot(xy(2,1),xy(2,2),'x','LineWidth',2,'Color','red');len=norm(lines(k).point1-lines(k).point2);if(len>max_len)max_len=len;xy_long=xy;endendplot(xy_long(:,1

35、),xy_long(:,2),'LineWidth',2,'Color','cyan');13.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(2,2,1);imshow(I1);title(' 灰度图像')axis(50,250,50,200);grid on;             

36、     %显示网格线axis on;                  %显示坐标系m,n=size(I1);                     

37、60;      %测量图像尺寸参数GP=zeros(1,256);                           %预创建存放灰度出现概率的向量for k=0:255     GP(k+1)=length(fin

38、d(I1=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')ylabel(' 出现概率')I2=im2bw(

39、I,150/255);  subplot(2,2,3),imshow(I2);title('阈值150的分割图像')axis(50,250,50,200);grid on;                  %显示网格线axis on;            &#

40、160;     %显示坐标系I3=im2bw(I,200/255);   %subplot(2,2,4),imshow(I3);title('阈值200的分割图像')axis(50,250,50,200);grid on;                  %显示网格线axis on;   

41、               %显示坐标系14. 自动阈值法：Otsu法用MATLAB实现Otsu算法：clcclear allI=imread('xian.bmp');subplot(1,2,1),imshow(I);title('原始图像')axis(50,250,50,200);grid on;         

42、0;        %显示网格线axis on;                  %显示坐标系level=graythresh(I);     %确定灰度阈值BW=im2bw(I,level);subplot(1,2,2),imshow(BW);title('Otsu 法阈值分割

43、图像')axis(50,250,50,200);grid on;                  %显示网格线axis on;                  %显示坐标系15.膨胀操作I=imread('xian.bm

44、p');          %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;                  

45、;%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);         &#

46、160;   %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;          &#

47、160;       %显示坐标系16.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;  &#

48、160;               %显示网格线axis on;                  %显示坐标系se=strel('disk',1);       %生成圆形结构元素

49、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);grid on;                  %显示网格线axis on;   &

50、#160;              %显示坐标系17.开启和闭合操作用 MATLAB实现开启和闭合操作I=imread('xian.bmp');          %载入图像subplot(2,2,1),imshow(I);title('原始图像');axis(50,250,50,200);axis on; 

51、60;                %显示坐标系I1=rgb2gray(I);subplot(2,2,2),imshow(I1);title('灰度图像');axis(50,250,50,200);axis on;                 &#

52、160;%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(I1,se);  

53、0;     %闭合操作subplot(2,2,3),imshow(I2);title('开启运算后图像');axis(50,250,50,200);axis on;                  %显示坐标系subplot(2,2,4),imshow(I3);title('闭合运算后图像');axis(50,250,50,200)

54、;axis on;                  %显示坐标系18.开启和闭合组合操作I=imread('xian.bmp');          %载入图像subplot(3,2,1),imshow(I);title('原始图像');axis(50,250,50,200);axis

55、 on;                  %显示坐标系I1=rgb2gray(I);subplot(3,2,2),imshow(I1);title('灰度图像');axis(50,250,50,200);axis on;               &

56、#160;  %显示坐标系                  se=strel('disk',1);    I2=imopen(I1,se);         %开启操作I3=imclose(I1,se);    

57、    %闭合操作subplot(3,2,3),imshow(I2);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(I3);title('闭合运算后图像');axis(50,250,50,200);axis on

58、;                  %显示坐标系se=strel('disk',1);I4=imopen(I1,se);I5=imclose(I4,se);subplot(3,2,5),imshow(I5);        %开闭运算图像title('开闭运算图像');axis(50,250,50,200

59、);axis on;                  %显示坐标系I6=imclose(I1,se);I7=imopen(I6,se);subplot(3,2,6),imshow(I7);        %闭开运算图像title('闭开运算图像');axis(50,250,50,200);axis on;                  %显示坐标系    19.