matlab经典代码大全

-哈哈哈MATLAB显示正炫余炫图：plot(x,y1,* r,x,y2,o b)定义【0,2】；t=0:pi/10:2*pi;定义函数文件：function 返回变量列表=函数名（输入变量列表）顺序结构：选择结构1）if-else-end语句其格式为：if 逻辑表达式程序模块1；else程序模块2；End图片读取：%选择图片路径filename, pathname = . uigetfile(*.jpg;*.bmp;*.gif,选择图片); %合成路径+文件名 str=pathname,filename;%为什么pathname和filename要前面出现的位置相反才能运行呢？%读取图片 im=imread(str); %使用图片 axes(handles.axes1); %显示图片 imshow(im);边缘检测：global im str=get(hObject,string);axes (handles.axes1);switch str case 原图 imshow(im); case sobel BW = edge(rgb2gray(im),sobel); imshow(BW); case prewitt BW = edge(rgb2gray(im),prewitt); imshow(BW); case canny BW = edge(rgb2gray(im),canny); imshow(BW); Canny算子边缘定位精确性和抗噪声能力效果较好，是一个折中方案end; 开闭运算：se=1,1,1;1,1,1;1,1,1;1,1,1; %Structuring ElementI=rgb2gray(im);imshow(I,);title(Original Image);I=double(I);im_height,im_width=size(I);se_height,se_width=size(se);halfheight=floor(se_height/2);halfwidth=floor(se_width/2);se_origin=floor(size(se)+1)/2);image_dilation=padarray(I,se_origin,0,both); %Image to be used for dilationimage_erosion=padarray(I,se_origin,256,both); %Image to be used for erosion% Dilation %for k=se_origin(1)+1:im_height+se_origin(1) for kk=se_origin(2)+1:im_width+se_origin(2) dilated_image(k-se_origin(1),kk-se_origin(2)=max(max(se+image_dilation(k-se_origin(1):k+halfheight-1,kk-se_origin(2):kk+halfwidth-1); endendfigure;imshow(dilated_image,);title(Image after Dilation);% Erosion %se=se;for k=se_origin(2)+1:im_height+se_origin(2) for kk=se_origin(1)+1:im_width+se_origin(1) eroded_image(k-se_origin(2),kk-se_origin(1)=min(min(image_erosion(k-se_origin(2):k+halfwidth-1,kk-se_origin(1):kk+halfheight-1)-se); endendfigure;imshow(eroded_image,);title(Image after Erosion);% Opening(Erosion first, then Dilation) %se=se;image_dilation2=eroded_image; %Image to be used for dilationfor k=se_origin(1)+1:im_height-se_origin(1) for kk=se_origin(2)+1:im_width-se_origin(2) opening_image(k-se_origin(1),kk-se_origin(2)=max(max(se+image_dilation2(k-se_origin(1):k+halfheight-1,kk-se_origin(2):kk+halfwidth-1); endendfigure;imshow(opening_image,);title(Opening Image);% Closing(Dilation first, then Erosion) %se=se;image_erosion2=dilated_image; %Image to be used for erosionfor k=se_origin(2)+1:im_height-se_origin(2) for kk=se_origin(1)+1:im_width-se_origin(1) closing_image(k-se_origin(2),kk-se_origin(1)=min(min(image_erosion2(k-se_origin(2):k+halfwidth-1,kk-se_origin(1):kk+halfheight-1)-se); endendfigure;imshow(closing_image,);title(Closing Image);Warning: Image is too big to fit on screen; displaying at 31% scale. In truesizeResize1 at 308 In truesize at 44 In imshow at 161图像的直方图归一化：I=imread(red.bmp);%读入图像figure;%打开新窗口 M,N=size(I);%计算图像大小 counts,x=imhist(I,32);%计算有32个小区间的灰度直方图 counts=counts/M/N;%计算归一化灰度直方图各区间的值 stem(x,counts);%绘制归一化直方图图像平移：I=imread(shuichi.jpg);se=translate(strel(1),180 190);B=imdilate(I,se);figure;subplot(1,2,1),subimage(I);title(原图像);subplot(1,2,2),subimage(B);title(平移后图像);图像的转置；A=imread(nir.bmp);tform=maketform(affine,0 1 0;1 0 0;0 0 1);B=imtransform(A,tform,nearest);figure;imshow(A);figure;imshow(B);imwrite(B,nir转置后图像.bmp); 图像滤波：B = imfilter(A,H,option1,option2,.)或写作g = imfilter(f, w, filtering_mode, boundary_options, size_options)其中，f为输入图像，w为滤波掩模，g为滤波后图像。filtering_mode用于指定在滤波过程中是使用“相关”还是“卷积”。boundary_options用于处理边界充零问题，边界的大小由滤波器的大小确定。具体参数选项见下表：选项描述filtering_modecorr通过使用相关来完成，该值为默认。conv通过使用卷积来完成boundary_optionsX输入图像的边界通过用值X（无引号）来填充扩展其默认值为0replicate图像大小通过复制外边界的值来扩展symmet