opencv-基于Matlab实现的opencv图像处理算法之POSHE直方图均衡化.zip

%% This is a function of BERF. %@ date ： 2019/4/27 %@ author ： Xiaowu %@ CSDN ：https://blog.csdn.net/weixin_40647819/article/details/88416512 %@ github ：https://github.com/2209520576/Image-Processing-Algorithm %/////////////////////////////////////////////////// %BERF滤波器 %src - 输入图像 %dst - 目标图像 %step_r - 子块垂直移动步长 %step_c - 子块水平移动步长 %step_levels - 灰度级缓慢变化的步长 %large_dir - 最大灰度差异 %////////////////////////////////////////////////// %% function dst=BERF(src, dst,step_r, step_c, step_levels, large_dir) [dstrows,dstcols]=size(dst); %处理子块的行边界（横向边界） for i=1:step_r:dstrows for j=1:dstcols if (i>1 && i<dstrows ) %图像边界判断，先排除第一行和最后一行 %块效应检查 dfacter_newsrc=abs(src(i,j)-src(i+1,j)) + abs(src(i,j)-src(i-1,j)); %原图子块边界与相邻两侧像素的灰度差异 dfacter_dst=abs(dst(i,j)-dst(i+1,j)) + abs(dst(i,j)-dst(i-1,j)); %POSHEed图子块边界与相邻两侧像素的灰度差异 if (abs(dfacter_dst - dfacter_newsrc) > step_levels) %存在块效应执行BERF b = 0; ave_bound=uint8( (uint16(dst(i - 1, j)) + uint16(dst(i + 1, j))) / 2 ); dst(i,j)=ave_bound; %垂直于子块边界，向上递增方向（ increasing rule） if (dst(i-1,j)> dst(i+1,j)) if (i - 2 - b >= 1) %图像边界判断(下一位置像素) pixel_present_add = dst(i - 1 - b, j); pixel_next_add = dst(i - 2 - b, j); pixel_present_add = ave_bound + step_levels; while(i - 2 - b >= 1 && pixel_next_add - pixel_present_add >= step_levels && pixel_next_add - pixel_present_add <= large_dir) pixel_next_add = pixel_present_add + step_levels; dst(i - 1 - b, j)=pixel_present_add;%%%%%% dst(i - 2 - b, j)=pixel_next_add;%%%%%% b =b+1; if(i - 2 - b >= 1) %图像边界判断(下一位置像素) pixel_present_add = dst(i - 1 - b, j); pixel_next_add = dst(i - 2 - b, j); end end end %垂直于子块边界，向下递减方向（ decreasing rule） b=0; if (i + 2 + b <=dstrows) pixel_present_dec = dst(i + 1 + b, j); pixel_next_dec = dst(i + 2 + b, j); pixel_present_dec = ave_bound - step_levels; while (i + 2 + b <=dstrows && pixel_present_dec - pixel_next_dec >= step_levels && pixel_present_dec - pixel_next_dec <= large_dir) pixel_next_dec = pixel_present_dec - step_levels; dst(i + 1 + b, j)=pixel_present_dec;%%%%%% dst(i + 2 + b, j)=pixel_next_dec;%%%%%% b = b+1; if (i + 2 + b <=dstrows) %图像边界判断 pixel_present_dec = dst(i + 1 + b, j); pixel_next_dec = dst(i + 2 + b, j); end end end end %垂直于子块边界，向下递增方向（ increasing rule） b=0; if (dst(i - 1, j) < dst(i + 1, j)) if (i + 2 + b <= dstrows) %图像边界判断 pixel_present_add = dst(i + 1 + b, j); pixel_next_add = dst(i + 2 + b, j); pixel_present_add = ave_bound + step_levels; while (i + 2 + b <= dstrows && pixel_next_add - pixel_present_add >= step_levels && pixel_next_add - pixel_present_add <= large_dir) pixel_next_add = pixel_present_add + step_levels; dst(i + 1 + b, j)=pixel_present_add;%%%%%% dst(i + 2 + b, j)=pixel_next_add;%%%%%% b =b + 1; if (i + 2 + b <= dstrows) %图像边界判断 pixel_present_add = dst(i + 1 + b, j); pixel_next_add = dst(i + 2 + b, j); end end end %垂直于子块边界，向上递减方向（ decreasing rule） b=0; if (i - 2 - b >= 1) pixel_present_dec = dst(i - 1 - b, j); pixel_next_dec = dst(i - 2 - b, j); pixel_present_dec = ave_bound - step_levels; while (i - 2 - b >= 1 && pixel_present_dec - pixel_next_dec >= step_levels && pixel_present_dec - pixel_next_dec <= large_dir) pixel_next_dec = pixel_present_dec - step_levels; dst(i - 1 - b, j)=pixel_present_dec;%%%%%% dst(i - 2 - b, j)=pixel_next_dec;%%%%%% b =b + 1; if (i - 2 - b >= 1) %图像边界判断 pixel_present_dec = dst(i - 1 - b, j); pixel_next_dec = dst(i - 2 - b, j); end end end end end end end end %处理子块的行边界（纵向向边界） for j=1:step_c:dstcols for i=1:dstrows if (j>1 && j<dstcols ) %图像边界判断，先排除第一列和最后一列 %块效应检查 dfacter_newsrc=abs(src(i,j)-src(i,j+1)) + abs(src(i,j)-src(i,j-1)); %原图子块边界与相邻两侧像素的灰度差异 dfacter_dst=abs(dst(i,j)-dst(i,j+1)) + abs(dst(i,j)-dst(i,j-1)); %POSHEed图子块边界与相邻两侧像素的灰度差异 if (abs(dfacter_dst - dfacter_newsrc) > step_levels) %存在块效应执行BERF b = 0; ave_bound=uint8( (uint16(dst(i, j-1)) + uint16(dst(i, j+1))) / 2 ); dst(i,j)=ave_bound; %垂直于子块边界，向左递增方向（ increasing rule） if (dst(i,j-1)> dst(i,j+1)) if (j - 2 - b >= 1) %图像边界判断(下一位置像素) pixel_present_add = dst(i,j - 1 - b); pixel_next_add = dst(i,j - 2 - b); pixel_present_add = ave_bound + step_levels; while(j - 2 - b >= 1 && pixel_next_add - pixel_present_add >= step_levels && pixel_next_add - pixel_present_add <= large_dir) pixel_next_add = pixel_present_add + step_levels; dst(i,j - 1 - b)=pixel_present_add;%%%%%% dst(i,j - 2 - b)=pixel_next_add;%%%%%% b =b+1; if(j - 2 - b >= 1) %图像边界判断(下一位置像素) pixel_present_add = dst(i,j - 1 - b); pixel_next_add = dst(i,j - 2 - b); end end end %垂直于子块边界，向右递减方向（ decreasing rule） b=0; if (j + 2 + b <dstcols) pixel_present_dec = dst(i,j + 1 + b); pixel_next_dec = dst(i,j + 2 + b); pixel_present_dec = ave_bound - step_levels; while (i + 2 + b < dstcols && pixel_present_dec - pixel_next_dec >= step_levels && pixel_present_dec - pixel_next_dec <= large_dir) pixel_next_dec = pixel_present_dec - step_levels; dst(i,j + 1 + b)=pixel_present_dec;%%%%%% dst(i,j + 2 + b)=pixel_next_dec;%%%%%%