图像增强算法

    DSIHE（等面积双子图像直方图均衡化）；
    RMSHE（基于递归平均分离直方图均衡化的对比度增强算法）；
    WTHE(基于权值阈值的直方图均衡算法) ；
    AMHE（自适应改进直方图均衡化）；
    RSIHE算法（递归子图像直方图均衡化）；
    红外图像直方图双向均衡技术研究
    
    
      
      
      
      
      
      
    

    %最早Kim在1997年提出BBHE算法[6]，为的是在增强图像对比度的同时保
    %持灰度图像的亮度,这种算法是将输入图像分成两个子图像，第一个图像
    %的灰度值拉伸到最小值和均值之间，第二个子图像灰度值调整到均值和最
    %大值之间。
    img=imread('D:\2.png');
    img=rgb2gray(img);
    imshow(img,[]);
    
    sz = size(img);
    
    o_mean = round(mean(img(:)));
    
    %  zhifangtu
    
    h_l = zeros(256,1);
    
    h_u = zeros(256,1);
    
    for i = 1:sz(1)
    for j = 1:sz(2)
        
        g_val = img(i,j);
        
        if(g_val<=o_mean)
           h_l(g_val+1) = h_l(g_val+1) + 1;
        else
            h_u(g_val+1) = h_u(g_val+1)+ 1;
        end
        
    end
    end
    
    % NORMALIZED HISTOGRAM OR PDF
    
    nh_l = h_l/sum(h_l);
    nh_u = h_u/sum(h_u);
    
    % CDF
    
    hist_l_cdf = double(zeros(256,1));
    hist_u_cdf = double(zeros(256,1));
    
    hist_l_cdf(1) = nh_l(1);
    hist_u_cdf(1) = nh_u(1);
    
    for k = 2:256
    hist_l_cdf(k) =  hist_l_cdf(k-1) + nh_l(k);
    hist_u_cdf(k) =  hist_u_cdf(k-1) + nh_u(k);
    end
    
    % IMAGE MODIFICATION图像修正
    
    equalized_img = zeros(sz);
    
    range_l = [0 o_mean];
    range_u = [(o_mean+1) 255];
    
    for i =1:sz(1)
    for j =1:sz(2)
        g_val = img(i,j);
        
        if(g_val<=o_mean)
           equalized_img(i,j) = range_l(1) + round(((range_l(2)-range_l(1))*hist_l_cdf(g_val+1))); 
        else
           equalized_img(i,j) = range_u(1) + round(((range_u(2)-range_u(1))*hist_u_cdf(g_val+1))); 
        end
        
    end
    end
    
    figure,imshow(uint8(equalized_img))
    title('BBHE的直方图');
    figure,imhist(uint8(equalized_img))
    title('BBHE的直方图');