Matlab traverses images, string arrays and other basic operations

Matlab Basic operation

1. Traversal image

1.1 Traverse the folder image

imgPath = 'E:/imageData/';        %  Image library path 
imgDir  = dir([imgPath '*.jpg']); %  Traverse all of jpg Format file 
for i = 1:length(imgDir)          %  You can process the pictures one by one by traversing the structure 
    img = imread([imgPath imgDir(i).name]); % Read each picture 
end

1.2 Traverse all images in the folder subdirectory

imgDataPath = 'E:/imageData/';
imgDataDir  = dir(imgDataPath);             %  Traverse all files 
for i = 1:length(imgDataDir)
    if(isequal(imgDataDir(i).name,'.')||... %  Remove the two hidden folders provided by the system 
       isequal(imgDataDir(i).name,'..')||...
       ~imgDataDir(i).isdir)                %  Remove those that are not folders in traversal 
           continue;
    end
    imgDir = dir([imgDataPath imgDataDir(i).name '/*.jpg']); 
    for j =1:length(imgDir)                 %  Go through all the pictures 
        img = imread([imgDataPath imgDataDir(i).name '/' imgDir(j).name]);
    end
end

2. Character array operations

The following code implements Gaussian filtering for images with different names

name={
    'Lena','Monarch','House'};// String cell array 
D={
    '10','20','30','40','50','75','100'};

for i=1:length(name)
    for j=1:length(D)
        [name{
    i},D{
    j}]// Read the content with braces {}, If you use （）, Then the output is still a cell array , It's not a string 
        path=['testimages\\',[name{
    i},D{
    j}],'.png'];// String splicing []
        img=imread(path);
        sigma=str2num(D{
    j});
        W = fspecial('gaussian',[sigma,sigma],1); 
        result = imfilter(img, W,'conv');
        psnr=getPSNR(img,result);
        imwrite(result,['testimages\\',[name{
    i},D{
    j}],'-psnr-',num2str(psnr),'.png']);
    end
end
// Calculate the peak signal-to-noise ratio 
function [psnr]=getPSNR(src,dst)
    diff=src-dst;
    MSE= sum(diff(:).*diff(:))/prod(size(src));
    psnr = 10*log10(255^2/MSE);
end

3. Looking for peaks

findpeaks  Find the peak function 
pks = findpeaks(data)
[pks,locs] = findpeaks(data) ------pks  Corresponding peak ,locs  Corresponding peak digits 
[...] = findpeaks(data,'minpeakheight',mph)----mph  Set the minimum height of the peak 
[...] = findpeaks(data,'minpeakdistance',mpd)----mpd  Set the minimum interval between two peaks 
[...] = findpeaks(data,'threshold',th)
[...] = findpeaks(data,'npeaks',np)
[...] = findpeaks(data,'sortstr',str)