數(shù)字圖像處理代碼大全

1、1.圖像反轉MATLAB程序實現(xiàn)如下：I=imread('xian.bmp');J=double(I);J=-J+(256-1); %圖像反轉線性變換H=uint8(J);subplot(1,2,1),imshow(I);subplot(1,2,2),imshow(H);2.灰度線性變換MATLAB程序實現(xiàn)如下：I=imread('xian.bmp');subplot(2,2,1),imshow(I);title('原始圖像');axis(50,250,50,200);axis on; %顯示坐標系I1=rgb2gray(I);subplot(2

2、,2,2),imshow(I1);title('灰度圖像');axis(50,250,50,200);axis on; %顯示坐標系J=imadjust(I1,0.1 0.5,); %局部拉伸，把0.1 0.5內的灰度拉伸為0 1subplot(2,2,3),imshow(J);title('線性變換圖像0.1 0.5');axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系K=imadjust(I1,0.3 0.7,); %局部拉伸，把0.3 0.7內的灰度拉伸為0 1subplot(2,2,4),imshow(

3、K);title('線性變換圖像0.3 0.7');axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系3.非線性變換MATLAB程序實現(xiàn)如下：I=imread('xian.bmp');I1=rgb2gray(I);subplot(1,2,1),imshow(I1);title('灰度圖像');axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系J=double(I1);J=40*(log(J+1);H=uint8(J);subplot(1,2,2),

4、imshow(H);title('對數(shù)變換圖像');axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系4.直方圖均衡化MATLAB程序實現(xiàn)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.線性平滑濾波器用MATLAB實現(xiàn)領域平均法

5、抑制噪聲程序：I=imread('xian.bmp');subplot(231)imshow(I)title('原始圖像')I=rgb2gray(I);I1=imnoise(I,'salt & pepper',0.02);subplot(232)imshow(I1)title('添加椒鹽噪聲的圖像')k1=filter2(fspecial('average',3),I1)/255; %進行3*3模板平滑濾波k2=filter2(fspecial('average',5),I1)/255; %

6、進行5*5模板平滑濾波k3=filter2(fspecial('average',7),I1)/255; %進行7*7模板平滑濾波k4=filter2(fspecial('average',9),I1)/255; %進行9*9模板平滑濾波subplot(233),imshow(k1);title('3*3模板平滑濾波');subplot(234),imshow(k2);title('5*5模板平滑濾波');subplot(235),imshow(k3);title('7*7模板平滑濾波');subplot(236)

7、,imshow(k4);title('9*9模板平滑濾波');6.中值濾波器用MATLAB實現(xiàn)中值濾波程序如下：I=imread('xian.bmp');I=rgb2gray(I);J=imnoise(I,'salt&pepper',0.02);subplot(231),imshow(I);title('原圖像');subplot(232),imshow(J);title('添加椒鹽噪聲圖像');k1=medfilt2(J); %進行3*3模板中值濾波k2=medfilt2(J,5,5); %進行5*5模板

8、中值濾波k3=medfilt2(J,7,7); %進行7*7模板中值濾波k4=medfilt2(J,9,9); %進行9*9模板中值濾波subplot(233),imshow(k1);title('3*3模板中值濾波');subplot(234),imshow(k2);title('5*5模板中值濾波');subplot(235),imshow(k3);title('7*7模板中值濾波');subplot(236),imshow(k4);title('9*9模板中值濾波');7.用Sobel算子和拉普拉斯對圖像銳化：I=imrea

9、d('xian.bmp');subplot(2,2,1),imshow(I);title('原始圖像');axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系I1=im2bw(I);subplot(2,2,2),imshow(I1);title('二值圖像');axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系H=fspecial('sobel'); %選擇sobel算子J=filter2(H,I1); %卷積運算subplot(2,

10、2,3),imshow(J);title('sobel算子銳化圖像');axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系h=0 1 0,1 -4 1,0 1 0; %拉普拉斯算子J1=conv2(I1,h,'same'); %卷積運算subplot(2,2,4),imshow(J1);title('拉普拉斯算子銳化圖像');axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系8.梯度算子檢測邊緣用MATLAB實現(xiàn)如下：I=imread('x

11、ian.bmp');subplot(2,3,1);imshow(I);title('原始圖像');axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系I1=im2bw(I);subplot(2,3,2);imshow(I1);title('二值圖像');axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系I2=edge(I1,'roberts');figure;subplot(2,3,3);imshow(I2);title('rober

12、ts算子分割結果');axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系I3=edge(I1,'sobel');subplot(2,3,4);imshow(I3);title('sobel算子分割結果');axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系I4=edge(I1,'Prewitt');subplot(2,3,5);imshow(I4);title('Prewitt算子分割結果');axis(50,250,50,

13、200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系9.LOG算子檢測邊緣用MATLAB程序實現(xiàn)如下：I=imread('xian.bmp');subplot(2,2,1);imshow(I);title('原始圖像');I1=rgb2gray(I);subplot(2,2,2);imshow(I1);title('灰度圖像');I2=edge(I1,'log');subplot(2,2,3);imshow(I2);title('log算子分割結果');10.Canny算子檢測邊緣用MATLAB程

14、序實現(xiàn)如下：I=imread('xian.bmp');subplot(2,2,1);imshow(I);title('原始圖像')I1=rgb2gray(I);subplot(2,2,2);imshow(I1);title('灰度圖像');I2=edge(I1,'canny');subplot(2,2,3);imshow(I2);title('canny算子分割結果');11.邊界跟蹤（bwtraceboundary函數(shù)）clcclear allI=imread('xian.bmp');figure

15、imshow(I);title('原始圖像');I1=rgb2gray(I); %將彩色圖像轉化灰度圖像threshold=graythresh(I1); %計算將灰度圖像轉化為二值圖像所需的門限BW=im2bw(I1, threshold); %將灰度圖像轉化為二值圖像figureimshow(BW);title('二值圖像');dim=size(BW);col=round(dim(2)/2)-90; %計算起始點列坐標row=find(BW(:,col),1); %計算起始點行坐標connectivity=8;num_points=180;contour=b

16、wtraceboundary(BW,row,col,'N',connectivity,num_points);%提取邊界figureimshow(I1);hold on;plot(contour(:,2),contour(:,1), 'g','LineWidth' ,2);title('邊界跟蹤圖像');12.Hough變換I= imread('xian.bmp');rotI=rgb2gray(I);subplot(2,2,1);imshow(rotI);title('灰度圖像');axis(50,

17、250,50,200);grid on; axis on;BW=edge(rotI,'prewitt');subplot(2,2,2);imshow(BW);title('prewitt算子邊緣檢測后圖像');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('霍夫變換圖'

18、;);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);,imsh

19、ow(rotI);title('霍夫變換圖像檢測');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','green');plot(xy(1,1),xy(1,2),'x','LineWidth',2,'Color','ye

20、llow');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),xy_long(:,2),'LineWidth',2,'Color','cyan');13.直方圖閾值法用MATLAB實現(xiàn)直方圖閾值法：I=im

21、read('xian.bmp');I1=rgb2gray(I);figure;subplot(2,2,1);imshow(I1);title('灰度圖像')axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系m,n=size(I1); %測量圖像尺寸參數(shù)GP=zeros(1,256); %預創(chuàng)建存放灰度出現(xiàn)概率的向量for k=0:255 GP(k+1)=length(find(I1=k)/(m*n); %計算每級灰度出現(xiàn)的概率，將其存入GP中相應位置endsubplot(2,2,2),bar(0:255,GP,&

22、#39;g') %繪制直方圖title('灰度直方圖')xlabel('灰度值')ylabel('出現(xiàn)概率')I2=im2bw(I,150/255); subplot(2,2,3),imshow(I2);title('閾值150的分割圖像')axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系I3=im2bw(I,200/255); %subplot(2,2,4),imshow(I3);title('閾值200的分割圖像')axis(50,250,50,200

23、);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系14. 自動閾值法：Otsu法用MATLAB實現(xiàn)Otsu算法：clcclear allI=imread('xian.bmp');subplot(1,2,1),imshow(I);title('原始圖像')axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系level=graythresh(I); %確定灰度閾值BW=im2bw(I,level);subplot(1,2,2),imshow(BW);title('Otsu法閾值分割圖像')

24、axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系15.膨脹操作I=imread('xian.bmp'); %載入圖像I1=rgb2gray(I);subplot(1,2,1);imshow(I1);title('灰度圖像') axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系se=strel('disk',1); %生成圓形結構元素I2=imdilate(I1,se); %用生成的結構元素對圖像進行膨脹subplot(1,2,2);imshow(

25、I2);title('膨脹后圖像');axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系16.腐蝕操作MATLAB實現(xiàn)腐蝕操作I=imread('xian.bmp'); %載入圖像I1=rgb2gray(I);subplot(1,2,1);imshow(I1);title('灰度圖像') axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系se=strel('disk',1); %生成圓形結構元素I2=imerode(I1,se);

26、%用生成的結構元素對圖像進行腐蝕subplot(1,2,2);imshow(I2);title('腐蝕后圖像');axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標系17.開啟和閉合操作用MATLAB實現(xiàn)開啟和閉合操作I=imread('xian.bmp'); %載入圖像subplot(2,2,1),imshow(I);title('原始圖像');axis(50,250,50,200);axis on; %顯示坐標系I1=rgb2gray(I);subplot(2,2,2),imshow(I1);t

27、itle('灰度圖像');axis(50,250,50,200);axis on; %顯示坐標系 se=strel('disk',1); %采用半徑為1的圓作為結構元素I2=imopen(I1,se); %開啟操作I3=imclose(I1,se); %閉合操作subplot(2,2,3),imshow(I2);title('開啟運算后圖像');axis(50,250,50,200);axis on; %顯示坐標系subplot(2,2,4),imshow(I3);title('閉合運算后圖像');axis(50,250,50,2

28、00);axis on; %顯示坐標系18.開啟和閉合組合操作I=imread('xian.bmp'); %載入圖像subplot(3,2,1),imshow(I);title('原始圖像');axis(50,250,50,200);axis on; %顯示坐標系I1=rgb2gray(I);subplot(3,2,2),imshow(I1);title('灰度圖像');axis(50,250,50,200);axis on; %顯示坐標系 se=strel('disk',1); I2=imopen(I1,se); %開啟操作I3

29、=imclose(I1,se); %閉合操作subplot(3,2,3),imshow(I2);title('開啟運算后圖像');axis(50,250,50,200);axis on; %顯示坐標系subplot(3,2,4),imshow(I3);title('閉合運算后圖像');axis(50,250,50,200);axis on; %顯示坐標系se=strel('disk',1);I4=imopen(I1,se);I5=imclose(I4,se);subplot(3,2,5),imshow(I5); %開閉運算圖像title('開閉運算圖像');axis(50,250,50,200);axis on; %顯示坐標系I6=imclose(I1,se);I7=imopen(I6,se);subplot(3,2,6),imshow(I7); %閉