matlab經(jīng)典代碼大全

-哈哈哈MATLAB顯示正炫余炫圖：plot(x,y1,* r,x,y2,o b)定義【0,2】；t=0:pi/10:2*pi;定義函數(shù)文件：function 返回變量列表=函數(shù)名（輸入變量列表）順序結(jié)構(gòu)：選擇結(jié)構(gòu)1）if-else-end語句其格式為：if 邏輯表達(dá)式程序模塊1；else程序模塊2；End圖片讀取：%選擇圖片路徑filename, pathname = . uigetfile(*.jpg;*.bmp;*.gif,選擇圖片); %合成路徑+文件名 str=pathname,filename;%為什么pathname和filename要前面出現(xiàn)的位置相反才能運(yùn)行呢？%讀取圖片 im=imread(str); %使用圖片 axes(handles.axes1); %顯示圖片 imshow(im);邊緣檢測：global im str=get(hObject,string);axes (handles.axes1);switch str case 原圖 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算子邊緣定位精確性和抗噪聲能力效果較好，是一個折中方案end; 開閉運(yùn)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圖像的直方圖歸一化：I=imread(red.bmp);%讀入圖像figure;%打開新窗口 M,N=size(I);%計算圖像大小 counts,x=imhist(I,32);%計算有32個小區(qū)間的灰度直方圖 counts=counts/M/N;%計算歸一化灰度直方圖各區(qū)間的值 stem(x,counts);%繪制歸一化直方圖圖像平移：I=imread(shuichi.jpg);se=translate(strel(1),180 190);B=imdilate(I,se);figure;subplot(1,2,1),subimage(I);title(原圖像);subplot(1,2,2),subimage(B);title(平移后圖像);圖像的轉(zhuǎn)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轉(zhuǎn)置后圖像.bmp); 圖像濾波：B = imfilter(A,H,option1,option2,.)或?qū)懽鱣 = imfilter(f, w, filtering_mode, boundary_options, size_options)其中，f為輸入圖像，w為濾波掩模，g為濾波后圖像。filtering_mode用于指定在濾波過程中是使用“相關(guān)”還是“卷積”。boundary_options用于處理邊界充零問題，邊界的大小由濾波器的大小確定。具體參數(shù)選項見下表：選項描述filtering_modecorr通過使用相關(guān)來完成，該值為默認(rèn)。conv通過使用卷積來完成boundary_optionsX輸入圖像的邊界通過用值X（無引號）來填充擴(kuò)展其默認(rèn)值為0replicate圖像大小通過復(fù)制外邊界的值來擴(kuò)展symmet