matlab实现AHE

在matlab中实现了自适应直方图均衡（AHE），亲测有效。

%this is the main function
clear
clc;
img=（（imread（‘24.jpg‘）））;
figure;
imshow（img）;
result=ahe（img8150）;
figure;
imshow（result）;

disp ‘done‘;
%%
function img_new=ahe（imggridlimit） 
    
    img_new=img; %img_new is the img after AHE
    [mn]=size（img）;  
    
    %ECR
    
    grid_cols=grid;
    grid_rows=grid;

    grid_width=int32（fix（m/grid_cols））;
    grid_height=int32（fix（n/grid_rows））;
    
    map=zeros（grid_colsgrid_rows256）;
    
    %for each gridwe create their mapping function
    for i=1:grid_cols
        for j=1:grid_rows
            map（ij:）=MakeHistogram（img1+（i-1）*grid_width1+（j-1）*grid_heightgrid_widthgrid_heightlimit）; 
        end
    end
    %interpolate
    %boundary cases I followed the Karel Zuiderveld‘s implement（C version）
    xi = 1; 
    for i = 1:grid_cols+1 
        if i == 1 
            subx = grid_width/2; 
            xu = 1; 
            xd = 1; 
        elseif i == grid_cols+1 
            subx = grid_width/2; 
            xu =  grid_cols; 
            xd =  grid_cols; 
        else 
            subx = grid_width; 
            xu = i - 1; 
            xd = i; 
        end 
        yi = 1; 
        for j = 1:grid_rows+1
            if j == 1 
                suby = grid_height/2; 
                yl = 1; 
                yr = 1; 
            elseif j == grid_rows+1
                suby = grid_height/2; 
                yl = grid_rows; 
                yr = grid_rows; 
            else 
                suby = grid_height; 
                yl = j - 1; 
                yr = j; 
            end 
            UL = map（xuyl:）; 
            UR = map（xuyr:）; 
            DL = map（xdyl:）; 
            DR = map（xdyr:）; 

            subimg = img（xi:xi+subx-1yi:yi+suby-1）; 
            subimg = Interpolate（subimgULURDLDRsubxsuby）; 
            img_new（xi:xi+subx-1yi:yi+suby-1） = subimg; 
            yi = yi + suby; 
        end 
        xi = xi + subx; 
    end 
end

%%
function map=MakeHistogram（imgstartxstartywidthheightlimit） 
%make histogram
hist=zeros（1256）; 
        for i=startx:startx+width-1 
            for j=starty:starty+height-1
                value=img（ij）;
                hist（value+1）=hist（value+1）+1;
            end 
        end 
%clip and allienate noise

        if （limit>0）
        excess = 0; 
        %get the excess
        for degree = 1:256 
            excess=excess+max（0hist（degree）-limit）; 
        end 
        ts=limit-excess/256;
        avginc=excess/256;
        %cut them and compensate other gray level
        for degree=1:256
            if （hist（degree）>limit）
                hist（degree）=limit;
            end
            %when compensatingshould not larger than limit
            if （hist（degree）>ts）
                excess=excess-（limit-hist（degree））;
                hist（degree）=limit;
            else
                hist（degree）=hist（deg

 属性            大小     日期    时间   名称
----------- ---------  ---------- -----  ----
     文件        4292  2019-04-07 21:37  two.m