一个matlab数字图像处理程序的解释

clc;                                                   %clc是清除command window里的内容
clear all;                                             %clear是清除workspace里的变量
close all;                                             %close all来关闭所有已经打开的图像窗口
image_ori = imread('skeleton_orig.bmp');               %读取图像数据
image_ori = rgb2gray(image_ori);                       % 将rgb模式转换成灰度图
figure;                                                %画图
subplot(,,);                                        %把区域分成2行4列，并把图像显示到第一个
imshow(image_ori);                                     %显示图像
title('a.original image');                             %显示标题
image_ext = [zeros(,);image_ori;zeros(,)]';    %分别在上下两边加一行,并转置
image_ext = [zeros(,);image_ext;zeros(,);]';   %分别在左右两边加一列，并转置
image_double = im2double(image_ext);                   %将imdata_add转换成双精度

% lapa_modelace Operating
lapa_mode = [-,-,-;-,,-;-,-,-];                %拉普拉斯变换用模板[-,-,-;-,,-;-,-,-];
lapa_mode = lapa_mode(:);                               %转换成列矩阵
for x = ::
    for y = ::
    A =image_double([x-:x+],[y-:y+]);               %从image_double中以（x,y）为中心取出一个3*3的矩阵
    image_lapa(x-,y-) = lapa_mode'*A(:);              %将取出的矩阵与模板进行拉普拉斯变换取得的值放在image_lapa的(x-1,y-1)位置
    end
end
subplot(,,);
imshow(image_lapa);
title('b.lapalace image');
subplot(,,);

%Sharpening Operating
image_ab_sha = image_lapa+im2double(image_ori);
imshow(image_ab_sha);
title('c.a+b sharpening image');

%Grads Operating
sobel_mode_1= [-,-,-;,,;,,];                     %定义梯度处理的一个掩膜
sobel_mode_1= sobel_mode_1(:);
sobel_mode_2 = [-,,;-,,;-,,];                    %定义梯度处理的另一个掩膜
sobel_mode_2 = sobel_mode_2(:);
for x = ::
    for y = ::
    A =image_double([x-:x+],[y-:y+]);
    mid_1(x-,y-) = sobel_mode_1'*A(:);
    mid_2(x-,y-) = sobel_mode_2'*A(:);
    end
end
image_grad = abs(mid_1)+abs(mid_2);                        %对gx、gy绝对值化，然后求和
subplot(,,);
imshow(image_grad);
title('d.grads image');

%Smoothing Operating
Mxy_Ext = [zeros(,);image_grad;zeros(,)];           %分别在上下两边加两行
Mxy_Ext = [zeros(,);Mxy_Ext';zeros(2,804)]';            %先将Mxy_Ext转置，然后分别在左右两边加一列，最后将所得结果再转置
Linear_smooth = ones(,);                                  %创建一个5*5矩阵，初始值全是1
Linear_smooth = Linear_smooth(:);                           %将矩阵Linear_smooth转换成列矩阵
for x = ::                                             %大循环，x从3--，步进是1
    for y = ::                                         %小循环，y从3--，步进是1
        A = Mxy_Ext([x-:x+],[y-:y+]);                   %以Emx_Ext（x,y）为中心，截取5*5矩阵复制到A中
        image_smooth(x-,y-) = Linear_smooth'*A(:);         %将获取的矩阵值各个值求和然后放在新矩阵image_smooth的(x-2,y-2)位置
    end
end
image_smooth = image_smooth/;                             %求平均值
subplot(,,);                                             %把区域分成1行4列，并把图像显示到第一个
imshow(image_smooth);                                       %显示图像
title('e.smoothing image');                                 %显示标题

%Masking Operating
image_mask = image_ab_sha.*image_smooth;                    %点乘
subplot(,,);
imshow(image_mask);
title('f.Masking image');

%Sharpening Operating
image_af_sha = im2double(image_ori) + image_mask;
subplot(,,);
imshow(image_af_sha);
title('g.a+f sharpening image');

%Exponential  Transform
image_fin = image_af_sha.^0.5;                              %幂律变换
subplot(,,);
imshow(image_fin);
title('h.final result');