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‎Pretreatment/Gray2RGB.m

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%============================================
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% 单通道图像呈现彩图效果
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% 其他通道用全黑图表示
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%===============================================
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clc
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clearvars
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close all
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tic
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[FileName, FilePath]=uigetfile('*.jpg;*.png;*.tif;*.img;*.bmp;','请选择一幅参考图片');
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image_name = [FilePath FileName];
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Iorg = imread(image_name);
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[rI, cI] = size(Iorg);
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Ir = zeros(rI, cI, 3);
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%-- 输入对话框，选择呈现颜色　--%
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% 1-红色; 2-绿色; 3-蓝色
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prompt = {'请输入呈现颜色（1红色; 2绿色; 3蓝色）'};
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title = '单通道图像呈现彩图效果';
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lines = [1]';
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def = {'1'};
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Channel_input = inputdlg(prompt, title, lines, def);
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Nc = str2double(Channel_input);
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%-----------------------------%
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Ir(:,:,Nc) = Iorg;
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%-- 保存图像　--%
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rf = [FilePath, 'RGB-', FileName];
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imwrite(uint8(Ir), rf);
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%--------------%
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toc

‎Pretreatment/Part_Divide.m

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file_path = 'D:\MATLAB\bin\IMAGES\R_G_Enhanced\G_Channel\G_target_1024_enhanced\';% 图像文件夹路径
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img_path_list = dir(strcat(file_path,'*.tif'));%获取该文件夹中所有jpg格式的图像
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img_num = length(img_path_list);%获取图像总数量
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img_num_need = img_num - 8;
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if img_num > 0 %有满足条件的图像
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for k = img_num_need + 1 : img_num %逐一读取图像
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image_name = img_path_list(k).name;% 图像名
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Im= imread(strcat(file_path,image_name));
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L = size(Im);
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height= 128 ;
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width= 128 ;
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max_row = floor(L(1)/height);
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max_col = floor(L(2)/width);
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seg = cell(max_row,max_col);
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%分块
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for row = 1:max_row
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for col = 1:max_col
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seg(row,col)= {Im((row-1)*height+1:row*height,(col-1)*width+1:col*width,:)};
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end
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end
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for i=1:max_row*max_col
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imwrite(seg{i},strcat('D:\MATLAB\bin\IMAGES\R_G_Partition\G_Part\test_target_1024_128\',int2str(i),'part_',image_name));
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end
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% 画出分块的边界
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% for row = 1:max_row
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% for col = 1:max_col
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% rectangle('Position',[160*(col-1),160*(row-1),160,160],...
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% 'LineWidth',2,'LineStyle','-','EdgeColor','r');
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% end
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% end
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% hold off
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end
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end
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‎Pretreatment/RBB.m

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file_path = 'D:/ALL_DataSet/R_G_Partition/R_Part/train_target/';% 图像文件夹路径
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img_path_list = dir(strcat(file_path,'*.tif'));%获取该文件夹中所有jpg格式的图像
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img_num = length(img_path_list);%获取图像总数量
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if img_num > 0 %有满足条件的图像
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for k = 1:img_num %逐一读取图像
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image_name = img_path_list(k).name;% 图像名
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img = imread(strcat(file_path,image_name));
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black = imread('D:/PycharmDOC/test_photo/all_black.tif');
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x = cat(3, img, black, black);
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Img_R_path = strcat('D:/ALL_DataSet/RBB/train/RBB_' ,image_name);
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imwrite(x ,Img_R_path);
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end
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end

‎Pretreatment/RGB_split.m

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file_path = 'D:/MATLAB/bin/IMAGES/Original_512/';% 图像文件夹路径
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img_path_list = dir(strcat(file_path,'*.tif'));%获取该文件夹中所有jpg格式的图像
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img_num = length(img_path_list);%获取图像总数量
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if img_num > 0 %有满足条件的图像
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for j = 1:img_num %逐一读取图像
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image_name = img_path_list(j).name;% 图像名
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Image = imread(strcat(file_path,image_name));
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I1=Image(:,:,2);%G通道
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Img_R_path = strcat('D:/MATLAB/bin/IMAGES/G_channel/original_512/' , 'gc_512_', image_name);
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%保存结果
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imwrite(I1,Img_R_path);
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end
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end

‎Pretreatment/RG_Enhance.m

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file_path_r = 'D:/ALL_DataSet/R_G_Partition/R_Part/train_target/';% 图像文件夹路径
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file_path_g = 'D:/ALL_DataSet/R_G_Partition/G_Part/train_target_1024_128/';% 图像文件夹路径
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img_path_list_r = dir(strcat(file_path_r,'*.tif'));%获取该文件夹中所有tif格式的图像
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img_path_list_g = dir(strcat(file_path_g,'*.tif'));%获取该文件夹中所有tif格式的图像
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img_num = length(img_path_list_r);%获取图像总数量
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if img_num > 0 %有满足条件的图像
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for k = 1:img_num %逐一读取图像
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image_name_r = img_path_list_r(k).name;%
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image_name_g = img_path_list_g(k).name;% 图像名
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imgr = imread(strcat(file_path_r,image_name_r));
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imgg = imread(strcat(file_path_g,image_name_g));
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black = imread('D:/PycharmDOC/test_photo/all_black.tif');
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x = cat(3, imgr, imgg, imgg);
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Img_R_path = strcat('D:/ALL_DataSet/RGGE/train/RGGE_' ,image_name_r);
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imwrite(x ,Img_R_path);
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end
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end

‎Pretreatment/ThreeCopy.m

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file_path = 'D:/ALL_DataSet/R_G_Partition/R_Part/train_input/';% 图像文件夹路径
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img_path_list = dir(strcat(file_path,'*.tif'));%获取该文件夹中所有jpg格式的图像
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img_num = length(img_path_list);%获取图像总数量
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if img_num > 0 %有满足条件的图像
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for k = 1:img_num %逐一读取图像
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image_name = img_path_list(k).name;% 图像名
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img = imread(strcat(file_path,image_name));
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x = repmat(img,[1,1,3]);%将单通道图片转换为三通道图片
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Img_R_path = strcat('D:/ALL_DataSet/ThreeFoldGrayRed/train_input/TCR_' ,image_name);
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imwrite(x ,Img_R_path);
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end
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end

‎Pretreatment/lighten_lashen.m

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file_path = 'D:/MATLAB/bin/IMAGES/R_G_SingleChannels/G_channel/original_1024/';% 图像文件夹路径
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img_path_list = dir(strcat(file_path,'*.tif'));%获取该文件夹中所有jpg格式的图像
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img_num = length(img_path_list);%获取图像总数量
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if img_num > 0 %有满足条件的图像
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for k = 1:img_num %逐一读取图像
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image_name = img_path_list(k).name;% 图像名
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Ipi = imread(strcat(file_path,image_name));
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% figure;
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% subplot(2,2,1);
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% imshow(uint8(Ipi));title('1024红色单通道');
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%
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% original512 = imread('D:\MATLAB\bin\IMAGES\R_channel\original512\rc_512_1-512pix-speed7-ave1.tif')
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% subplot(2,2,2)
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% imshow(original512);title('512红色单通道')
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%-- ！！！！整体加亮！！！！ --%
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CL = 54;
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Ipi_CL = Ipi + CL;
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% subplot(2,2,3);
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% imshow(uint8(Ipi_CL));title('整体加亮效果');
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%-----------------------------%
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%-- ！！！！非线性灰度拉伸！！！！--%
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% gamma < 1 低灰度区强拉伸，高灰度区弱拉伸甚至压缩
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Ipi_histequ = imadjust(Ipi_CL, [57/255, 150/255], [40/255, 255/255], 0.85);
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% subplot(2,2,4)
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% imshow(uint8(Ipi_histequ));title('非线性灰度拉伸');
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Img_R_path = strcat('D:/MATLAB/bin/IMAGES/R_G_Enhanced/G_Channel/G_target_1024_enhanced/' ,image_name);
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imwrite(Ipi_histequ ,Img_R_path);
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end
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end

‎Pretreatment/mpmRGBimadjust.m

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%======================================================
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% MPM灰度均衡
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% f1=imadjust（f，[low_in high_in],[low_out high_out],gamma）
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%=======================================================
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clc
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close all
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clearvars
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tic
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[FileName, FilePath]=uigetfile('*.jpg;*.png;*.tif;*.img;*.bmp;','请选择一幅参考图片');
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image_name = [FilePath FileName];
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Iorg = imread(image_name);
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[rI, cI] = size(Iorg(:,:,1));
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%-- 判断图像信息所在的通道 --%
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ifocus = zeros(1,3); % 需要处理的分量，初始值为0，对应分量有值时，元素变为1 [0,0,0]
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for i=1:3 % i=1红色 ; i=2绿色; i=3蓝色
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Inidraw = Iorg(:,:,i); %通道读取
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Meani = mean(Inidraw(:)); %先把矩阵转化为向量，然后计算均值
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if(Meani>1) % 该分量有信息，理论上应该大于0就说明有信息，但是为了去噪，设成略大的值
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ifocus(i) = 1;
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end
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end
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%---------------------------%
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[r,c,v] = find(ifocus~=0);
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%%
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% 只处理有信息的分量
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Ir = zeros(rI, cI, 3);
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for i=2
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Ipi = Iorg(:,:,c(i));
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figure;
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subplot(2,2,1);
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imshow(uint8(Ipi));title('1024绿色单通道');
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original512 = imread('D:\MATLAB\bin\IMAGES\R_G_SingleChannels\G_channel\original_512\gc_512_1-512pix-speed7-ave1.tif')
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subplot(2,2,2)
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imshow(original512);title('512绿色单通道')
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%-- ！！！！整体加亮！！！！ --%
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CL = 54;
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Ipi_CL = Ipi + CL;
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subplot(2,2,3);
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imshow(uint8(Ipi_CL));title('整体加亮效果');
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%-----------------------------%
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%-- ！！！！非线性灰度拉伸！！！！--%
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% gamma < 1 低灰度区强拉伸，高灰度区弱拉伸甚至压缩
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Ipi_histequ = imadjust(Ipi_CL, [57/255, 150/255], [40/255, 255/255], 0.85);
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subplot(2,2,4)
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imshow(uint8(Ipi_histequ));title('非线性灰度拉伸');
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%---------------------------------%
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Ir(:,:,i) = Ipi_histequ;
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%-- 灰度直方图(原图) --%
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%[count_pi, x_pi] = imhist(Ipi); % xn是灰度值，count_n是出现的次数
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%[count_ri, x_ri] = imhist(Ir(:,:,i));
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%f_pi = count_pi/(rI*cI); % 出现次数归一化
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%f_ri = count_ri/(rI*cI);
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figure
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subplot(2,2,1);
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% stem(x_pi, f_pi, 'b.');
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imhist(Ipi);
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title('灰度直方图-原图');
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subplot(2,2,2);
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imhist(Ipi_CL);title('灰度直方图-整体加亮');
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subplot(2,2,3);
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% stem(x_ri, f_ri, 'r.');
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imhist(uint8(Ir(:,:,i)));
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title('灰度直方图-均衡后');
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%-----------------------------%
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%-----------------------------%
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figure
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IpiShow = zeros(rI,cI,3);
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IpiShow(:,:,i) = Ipi;
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imshow(uint8(IpiShow));title('原始RGB图');
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figure
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IriShow = zeros(rI,cI,3);
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IriShow(:,:,i) = Ipi_histequ;
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imgs = uint8(IriShow);
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imshow(uint8(IriShow));title('增亮＋非线性拉伸RGB图');
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%-----------------------------%
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%-- 保存图像　--%
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switch i
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case 1
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ChannelName = 'R-';
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case 2
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ChannelName = 'G-';
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case 3
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ChannelName = 'B-';
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end
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rfpi = [FilePath, 'org-', ChannelName, FileName];
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imwrite(uint8(IpiShow), rfpi);
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rfri = [FilePath, 'Heq-', ChannelName, FileName];
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I1 = imgs(:,:,1);
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imwrite(I1, rfri);
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%--------------%
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end
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toc

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