基于MATLAB的直方图去雾设计（数字图像处理）

一、全局直方图去雾

unction In = RemoveFogByGlobalHisteq(I, flag) if nargin < 2 flag = 1; end R = I(:,:,1); G = I(:,:,2); B = I(:,:,3); M = histeq(R); N = histeq(G); L = histeq(B); In = cat(3, M, N, L); if flag figure; subplot(2, 2, 1); imshow(I); title('原图像', 'FontWeight', 'Bold'); subplot(2, 2, 2); imshow(In); title('处理后的图像', 'FontWeight', 'Bold'); Q = rgb2gray(I); W = rgb2gray(In); subplot(2, 2, 3); imhist(Q, 64); title('原灰度直方图', 'FontWeight', 'Bold'); subplot(2, 2, 4); imhist(W, 64); title('处理后的灰度直方图', 'FontWeight', 'Bold'); end

实现效果如下

二、局部直方图去雾

function In = RemoveFogByLocalHisteq(I, flag) g1 = GetLocalHisteq(I(:, :, 1)); g2 = GetLocalHisteq(I(:, :, 2)); g3 = GetLocalHisteq(I(:, :, 3)); In = cat(3, g1, g2, g3); if flag figure; subplot(2, 2, 1); imshow(I); title('原图像', 'FontWeight', 'Bold'); subplot(2, 2, 2); imshow(In); title('处理后的图像', 'FontWeight', 'Bold'); Q = rgb2gray(I); W = rgb2gray(In); subplot(2, 2, 3); imhist(Q, 64); title('原灰度直方图', 'FontWeight', 'Bold'); subplot(2, 2, 4); imhist(W, 64); title('处理后的灰度直方图', 'FontWeight', 'Bold'); end

实现效果

三、RETINEX算法去雾

function In = RemoveFogByRetinex(f, flag) % 用Retinex的MSR实现图像去雾 % 输入参数： % f——图像矩阵 % flag——显示标记 % 输出参数： % In——结果图像 if nargin < 2 flag = 1; end %提取图像的R、G、B分量 fr = f(:, :, 1); fg = f(:, :, 2); fb = f(:, :, 3); %数据类型归一化 mr = mat2gray(im2double(fr)); mg = mat2gray(im2double(fg)); mb = mat2gray(im2double(fb)); %定义alpha参数 alpha = 1200; %定义模板大小 n = 128; %计算中心 n1 = floor((n+1)/2); for i = 1:n for j = 1:n %高斯函数 b(i,j) = exp(-((i-n1)^2+(j-n1)^2)/(4*alpha))/(pi*alpha); end end %卷积滤波 nr1 = imfilter(mr,b,'conv', 'replicate'); ng1 = imfilter(mg,b,'conv', 'replicate'); nb1 = imfilter(mb,b,'conv', 'replicate'); ur1 = log(nr1); ug1 = log(ng1); ub1 = log(nb1); tr1 = log(mr); tg1 = log(mg); tb1 = log(mb); yr1 = (tr1-ur1)/3; yg1 = (tg1-ug1)/3; yb1 = (tb1-ub1)/3; %定义beta参数 beta = 55; %定义模板大小 x = 32; %计算中心 x1 = floor((n+1)/2); for i = 1:n for j = 1:n %高斯函数 a(i,j) = exp(-((i-n1)^2+(j-n1)^2)/(4*beta))/(6*pi*beta); end end %卷积滤波 nr2 = imfilter(mr,a,'conv', 'replicate'); ng2 = imfilter(mg,a,'conv', 'replicate'); nb2 = imfilter(mb,a,'conv', 'replicate'); ur2 = log(nr2); ug2 = log(ng2); ub2 = log(nb2); tr2 = log(mr); tg2 = log(mg); tb2 = log(mb); yr2 = (tr2-ur2)/3; yg2 = (tg2-ug2)/3; yb2 = (tb2-ub2)/3; %定义eta参数 eta = 13944.5; %定义模板大小 l = 500; %计算中心 l1 = floor((n+1)/2); for i = 1:n for j = 1:n %高斯函数 e(i,j) = exp(-((i-n1)^2+(j-n1)^2)/(4*eta))/(4*pi*eta); end end %卷积滤波 nr3 = imfilter(mr,e,'conv', 'replicate'); ng3 = imfilter(mg,e,'conv', 'replicate'); nb3 = imfilter(mb,e,'conv', 'replicate'); ur3 = log(nr3); ug3 = log(ng3); ub3 = log(nb3); tr3 = log(mr); tg3 = log(mg); tb3 = log(mb); yr3 = (tr3-ur3)/3; yg3 = (tg3-ug3)/3; yb3 = (tb3-ub3)/3; dr = yr1+yr2+yr3; dg = yg1+yg2+yg3; db = yb1+yb2+yb3; cr = im2uint8(dr); cg = im2uint8(dg); cb = im2uint8(db); % 集成处理后的分量得到结果图像 In = cat(3, cr, cg, cb); %结果显示 if flag figure; subplot(2, 2, 1); imshow(f); title('原图像', 'FontWeight', 'Bold'); subplot(2, 2, 2); imshow(In); title('处理后的图像', 'FontWeight', 'Bold'); % 灰度化，用于计算直方图 Q = rgb2gray(f); M = rgb2gray(In); subplot(2, 2, 3); imhist(Q, 64); title('原灰度直方图', 'FontWeight', 'Bold'); subplot(2, 2, 4); imhist(M, 64); title('处理后的灰度直方图', 'FontWeight', 'Bold'); end

实现效果如下

 

以上是图片处理用到的主要程序代码，还需要进行整合才可以完全实现。

可以下载完整工程文件到https://download.csdn.net/download/lc886/12567110