数字图像处理代码大全

1、1.图像反转MATLAB程序实现如下:匸imread(xia n.bmp);J=double(l);J=-J+(256-1);H=ui nt8(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(xia n.bmp);subplot(2,2,1),imshow(I); title(原始图像);axis(50,250,50,200);axis on;I1= rgb2gray(l);subplot(2,2,2),imshow(I1); title(灰度图像);axis(50,250,

2、50,200);axis on;J=imadjust(l1,0.1 0.5,); % 为0 1%图像反转线性变换%显示坐标系%显示坐标系局部拉伸，把0.1 0.5内的灰度拉伸subplot(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(l1,0.3 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);g

3、rid 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：I=imread(xia n.bmp);I1= rgb2gray(l); 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J=double(I1);J=40*(log(J+1);H=ui nt8(J);subplot(1,2,2),imshow(H); title(对数变换图像);%显示网格线%显示坐标系axis(50,250,50,200);grid on;axis on;4

4、.直方图均衡化MATLAB程序实现如下：I=imread(xia n.bmp);I=rgb2gray(I);figure;subplot(2,2,1);imshow(I);subplot(2,2,2);imhist(I);I仁 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: 匸imread(xia n.bmp);subplot(231)imshow(l)title(原始图像)I=rgb2gray(I);I1=im noise(l,salt &

5、 pepper,0.02);subplot(232)imshow(I1)%进行3*3模%进行5*5模波%进行7*7模%进行9*9模title(添加椒盐噪声的图像)k1=filter2(fspecial(average,3),l1)/255;板平滑滤波k2=filter2(fspecial(average,5),l1)/255;k3=filter2(fspecial(average,7),l1)/255;板平滑滤波k4=filter2(fspecial(average,9),l1)/255;板平滑滤波模板平滑滤波);模板平滑滤波);模板平滑滤波);subplot(233),imshow(k1);

6、title(3*3subplot(234),imshow(k2);title(5*5subplot(235),imshow(k3);title(7*7subplot(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: 匸imread(xia n.bmp);匸rgb2gray(l);J=imno ise(l,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

7、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);title(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(xia n.b

8、mp);subplot(2,2,1),imshow(I);title(原始图像);axis(50,250,50,200);grid on;axis on;I仁im2bw(l);%显示网格线%显示坐标系subplot(2,2,2),imshow(l1); title(二值图像);axis(50,250,50,200);grid on;axis on;H=fspecial(sobe l);J=filter2(H,l1); subplot(2,2,3),imshow(J); title(sobel算子锐化图像 axis(50,250,50,200);grid on;axis on;h=0 1 0,1

9、 -4 1,0 1 0;J1=co nv2(l1,h,same);%显示网格线%显示坐标系%选择sobel算子%卷积运算);%显示网格线%显示坐标系%拉普拉斯算子%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8.梯度算子检测边缘用MATLAB实现如下:匸imread(xia n.bmp);subplot(2,3,1);imshow(l);title（原始图像）;axis(50,250,50,200);grid on;%显示网格线axis on;%显

10、示坐标系I1=im2bw (I);subplot(2,3,2);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I2=edge(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;%显示坐标系I3=edge(l1,sobel);subplot(2,3,4);imshow(l3);title（sobel算子分割结果）;axis(50,250,

11、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9.LOG算子检测边缘用MATLAB程序实现如下：I=imread(xia n.bmp);subplot(2,2,1);imshow(I);title（原始图像）;11= rgb2gray(l); subplot(2,2,2); imshow(ll);title(灰度图像);I2=edge(l1,

12、log); subplot(2,2,3);imshow(I2); title(log算子分割结果);1O.Canny算子检测边缘用MATLAB程序实现如下：l=imread(xia n.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,ca nn y);subplot(2,2,3);imshow(I2);title(canny算子分割结果);%将彩色图像转化灰度图像%计算将灰度图像转化为二%将灰度图像转化为二值图%计算起始点列坐标%

13、计算起始点行坐标11. 边界跟踪(bwtraceboundary 函数)clc clear all匸imread(xia n.bmp);figureimshow(I);title(原始图像);11= rgb2gray(l);threshold=graythresh(l1);值图像所需的门限BW=im2bw(l1, threshold); 像figureimshow(BW);title(二值图像); dim=size(BW);col=ro un d(dim(2)/2)-90; row=fi nd(BW(:,col),1);conn ectivity=8;nu m_po in ts=180;con

14、 tour=bwtracebo un dary(BW,row,col,N,c onn ectivity, num_p oin ts);%提取边界 figureimshow(ll);hold on;plot(contour(:,2),contour(:,1), g,LineWidth ,2); title(边界跟踪图像);12. Hough 变换I= imread(xia n.bmp);rotl=rgb2gray(l);subplot(2,2,1);imshow(rotI);title(灰度图像);axis(50,250,50,200);grid on;axis on;BW=edge(rotI,

15、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);axis on , axis no rmal, hold on;P=houghpeaks(H,5,threshold,ceil(0.3*max(H(:);x=T(P

16、(:,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(rotI);title(霍夫变换图像检测)；axis(50,250,50,200);grid on;axis on;hold on;max_le n=0;for k=1:le ngth(li nes)xy=li nes(k).poi nt1;li nes(k).poi nt2;plot(xy(:,1),xy(:,2),Li neWidth,2,Color,gree n)

17、;plot(xy(1,1),xy(1,2),x,Li neWidth,2,Color,yellow);plot(xy(2,1),xy(2,2),x,Li neWidth,2,Color,red);Ien=n orm(li nes(k).poi nt1-li nes(k).poi nt2);if(le n max_le n)max_le n=le n;xyon g=xy;endendplot(xy_lo ng(:,1),xy_lo ng(:,2),L in eWidth,2,Color,cya n);13. 直方图阈值法用MATLAB实现直方图阈值法：I=imread(xia n.bmp);11

18、= rgb2gray(I);figure;subplot(2,2,1);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%测量图像尺寸%预创建存放m,n=size(l1);参数GP=zeros(1,256);灰度出现概率的向量for k=0:255%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)方图title（灰度直方图）xlabel(灰度值)ylabel（出现概率）I2=im2bw(I,150/255);subplot(2,2,3)

19、,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;%显示坐标系l3=im2bw(l,200/255);%GP(k+1)=le ngth(fi nd(l1=k)/(m* n);%绘制直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;%显示坐标系14.自动阈值法：Otsu法用MATLAB实现Otsu算法:clc clear all匸imread(xia n.bmp);subplot(1,

20、2,1),imshow(l);title(原始图像)axis(50,250,50,200);grid on;axis on;level=graythresh(l);BW=im2bw(l,level);%显示网格线%显示坐标系%确定灰度阈值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I=imread(xia n.bmp);I1= rgb2gray(I); subplot(1,2,1); imshow(I1);title(灰度图像)%载入图像ax

21、is(50,250,50,200);grid on;axis on;se=strel(disk,1);I2=imdilate(l1,se);行膨胀subplot(1,2,2);imshow(l2);title(膨胀后图像);axis(50,250,50,200);grid on;axis on;16.腐蚀操作MATLAB实现腐蚀操作I=imread(xia n.bmp);I1= rgb2gray(I);subplot(1,2,1);imshow(I1);title(灰度图像)axis(50,250,50,200);grid on;axis on;%显示网格线%显示坐标系%生成圆形结构元素%用生

22、成的结构元素对图像进%显示网格线%显示坐标系%载入图像%显示网格线%显示坐标系se=strel(disk,1);%生成圆形结构元素%用生成的结构元素对图像进行腐%显示网格线%显示坐标系I2=imerode(l1,se);蚀subplot(1,2,2);imshow(l2);title(腐蚀后图像);axis(50,250,50,200);grid on;axis on;17.开启和闭合操作用MATLAB实现开启和闭合操作I=imread(xia n.bmp);% 载入图像subplot(2,2,1),imshow(I);title(原始图像);axis(50,250,50,200);axis

23、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;%显示坐标系se=strel(disk,1);%采用半径为1的圆作为结构元素I2=imope n(l1,se);%开启操作I3=imclose(l1,se);%闭合操作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subplot(2,2,4),imshow(I3);title（闭合运算后图像）;axis(50,2

24、50,50,200);axis on;%显示坐标系18.开启和闭合组合操作I=imread(xia n.bmp);%载入图像subplot(3,2,1),imshow(I);title（原始图像）;axis(50,250,50,200);axis on;%显示坐标系I1= rgb2gray(l);subplot(3,2,2),imshow(I1);title（灰度图像）;axis(50,250,50,200);axis on;%显示坐标系se=strel(disk,1);I2=imope n(l1,se);%开启操作I3=imclose(l1,se);%闭合操作subplot(3,2,3),i

25、mshow(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(I3);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=imope n(l1,se);I5=imclose(I4,se);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=imope n(l6,se);subplot(3,2,6),imshow(I7);%闭一开运算图像title（闭一开运算图像）;ax