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深度学习遥感影像分类(1)_数据集批量准备

2024-11-02 20:18:39   207人阅读

近年来，深度学习在遥感影像地物分类中取得了一系列显著的效果。CNN可以很好的获取影像纹理信息，捕捉像素与像素之间的空间特征，因此，一个训练好的深度学习模型在地物提取中具有很大的优势。但模型的训练却是一个很繁琐的任务，需要人工准备数据集，贴标签，训练模型等。本文将以sar影像为例实现冰水二分类的数据集批量准备工作（划线取点截取小图片保存）：

1.原始sar遥感影像技术分享

2.预处理思路：

     a.人工划线：对应在冰和水上画n条线（自己设置，注意自己需要针对类别所占比例控制线条数量和长度）

     b.保存小图片：获取直线上点坐标，以每个像素点为中心取21×21的小图片（类似mnist数据集，尺寸自己设置），保存至文件夹

     c. 创建label：以保存的小图片名称+空格+类别（0或者1）将label保存至新创建的txt文档中

3.代码实现：

     a.创建一个main函数调用drawTrainingSamples(img);CreateTrainSmallImages(img);drawValSamples(img);CreateValSmallImages(img);这四个函数，功能分别是和划训练集，创建训练集，划验证集，创建验证集

clear ;
clc;

img = imread(‘150905_multilook_4_s1a-ew-grd-hv-20150905t174712-20150905t174812-007583-00a7f0-002.tiff‘);
%准备训练集数据
drawTrainingSamples(img);
CreateTrainSmallImages(img);

%准备验证集数据
drawValSamples(img);
CreateValSmallImages(img);

      b.drawTrainingSamples(img)

function [] = drawTrainingSamples(img)
n_ice=4;
n_water=4;
h_im=imshow(img);
bw_train_ice=zeros(size(img));
bw_train_water=zeros(size(img));
fprintf(‘please draw four lines on the picture for preparing the training sets of Ice‘);
for i = 1:n_ice
    h = imline;
    bw = createMask(h,h_im);
    bw_train_ice=bw_train_ice+bw;
end
figure,imshow(bw_train_ice);

 h_im=imshow(img);
 fprintf(‘please draw four lines on the picture for preparing the training sets of Water‘);
 for i = 1:n_water
    h = imline;
    bw = createMask(h,h_im);
    bw_train_water=bw_train_water+bw;
 end
figure,imshow(bw_train_water);

 save(‘bw_train_ice.mat‘,‘bw_train_ice‘);
 save(‘bw_train_water.mat‘,‘bw_train_water‘);

       c.CreateTrainSmallImages(img)

function [] = CreateTrainSmallImages(img)

%创建小图片
      load bw_train_ice;
      load bw_train_water;
       fprintf(‘Creating training small images...‘);
        [X,Y]=find(bw_train_ice==1);
        A=[X,Y];
        A;
        [a,b]=size(A);
        mkdir(‘train‘);
        
            for i=1:a
                    m=A(i,1);
                    n=A(i,2);
                    SmallImage=img(m-10:m+10,n-10:n+10);
                    imwrite(SmallImage,[‘train/‘,num2str(i),‘.jpg‘]);
                     
                    fid = fopen(‘train.txt‘, ‘a‘);  
                    t=[num2str(i),‘.jpg‘];
                    fprintf(fid, ‘%s %d \n‘, t,0);  
                    fclose(fid); 
            end
            
        [X,Y]=find(bw_train_water==1);
        B=[X,Y];
        B;
        [a,b]=size(B);
        
            for j=1:a
                    m=B(j,1);
                    n=B(j,2);
                    SmallImage=img(m-10:m+10,n-10:n+10);
		             j=i+j;
                    imwrite(SmallImage,[‘train/‘,num2str(j),‘.jpg‘]);
                     
                    fid = fopen(‘train.txt‘, ‘a‘);  
                    t=[num2str(j),‘.jpg‘];
                    fprintf(fid, ‘%s %d \n‘, t,1);  
                    fclose(fid); 
                     
            end
end

       d.drawValSamples(img)

function [] = drawValSamples(img)
n_ice=4;
n_water=4;
h_im=imshow(img);
bw_val_ice=zeros(size(img));
bw_val_water=zeros(size(img));
fprintf(‘please draw four lines on the picture for preparing the validition sets of Ice‘);
for i = 1:n_ice
    h = imline;
    bw = createMask(h,h_im);
    bw_val_ice=bw_val_ice+bw;
end
figure,imshow(bw_val_ice);

 h_im=imshow(img);
 fprintf(‘please draw four lines on the picture for preparing the validition sets of Water‘);
 for i = 1:n_water
    h = imline;
    bw = createMask(h,h_im);
    bw_val_water=bw_val_water+bw;
 end
figure,imshow(bw_val_water);

 save(‘bw_val_ice.mat‘,‘bw_val_ice‘);
 save(‘bw_val_water.mat‘,‘bw_val_water‘);

       e.CreateValSmallImages(img)

function [] = CreateValSmallImages(img)

%创建小图片
      load bw_val_ice;
      load bw_val_water;

        [X,Y]=find(bw_val_ice==1);
        A=[X,Y];
        A;
        [a,b]=size(A);
        mkdir(‘val‘);
          fprintf(‘Creating validition sets small images...‘);
            for i=1:a
                    m=A(i,1);
                    n=A(i,2);
                    SmallImage=img(m-10:m+10,n-10:n+10);
                    imwrite(SmallImage,[‘val/‘,num2str(i),‘.jpg‘]);
                     
                    fid = fopen(‘val.txt‘, ‘a‘);  
                    t=[num2str(i),‘.jpg‘];
                    fprintf(fid, ‘%s %d \n‘, t,0);  
                    fclose(fid); 
            end
            
        [X,Y]=find(bw_val_water==1);
        B=[X,Y];
        B;
        [a,b]=size(B);
        
            for j=1:a
                    m=B(j,1);
                    n=B(j,2);
                    SmallImage=img(m-10:m+10,n-10:n+10);
		            j=i+j;
                    imwrite(SmallImage,[‘val/‘,num2str(j),‘.jpg‘]);
                     
                    fid = fopen(‘val.txt‘, ‘a‘);  
                    t=[num2str(j),‘.jpg‘];
                    fprintf(fid, ‘%s %d \n‘, t,1);  
                    fclose(fid); 
                     
            end
end

 

深度学习遥感影像分类(1)_数据集批量准备


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