资源简介
ROF去噪,图像处理,matlab源码
包含文献
代码片段和文件信息
%% ROFdenoise
%
% This denoising method is based on total-variation originally proposed by
% Rudin Osher and Fatemi. In this particular case fixed point iteration
% is utilized.
%
% For the included image a fairly good result is obtained by using a
% theta value around 12-16. A possible addition would be to analyze the
% residual with an entropy function and add back areas that have a lower
% entropy i.e. there are some correlation between the surrounding pixels.
%
% Philippe Magiera & Carl L鰊dahl 2008
%
function A = ROFdenoise(Image Theta)
[Image_h Image_w] = size(Image);
g = 1; dt = 1/4; nbrOfIterations = 5;
Image = double(Image);
p = zeros(Image_hImage_w2);
d = zeros(Image_hImage_w2);
div_p = zeros(Image_hImage_w);
for i = 1:nbrOfIterations
for x = 1:Image_w
for y = 2:Image_h-1
div_p(yx) = p(yx1) - p(y-1x1);
end
end
for x = 2:Image_w-1
for y = 1:Image_h
div_p(yx) = div_p(yx) + p(yx2) - p(yx-12);
end
end
% Handle boundaries
div_p(:1) = p(:12);
div_p(:Image_w) = -p(:Image_w-12);
div_p(1:) = p(1:1);
div_p(Image_h:) = -p(Image_h-1:1);
% Update u
u = Image-Theta*div_p;
% Calculate forward derivatives
du(::2) = u(:[2:Image_w Image_w])-u;
du(::1) = u([2:Image_h Image_h]:)-u;
% Iterate
d(::1) = (1+(dt/Theta/g).*abs(sqrt(du(::1).^2+du(::2).^2)));
d(::2) = (1+(dt/Theta/g).*abs(sqrt(du(::1).^2+du(::2).^2)));
p = (p-(dt/Theta).*du)./d;
end
A = u;
属性 大小 日期 时间 名称
----------- --------- ---------- ----- ----
文件 182633 2008-12-11 22:35 noisy.jpg
目录 0 2008-12-11 23:25 __MACOSX\
文件 82 2008-12-11 22:35 __MACOSX\._noisy.jpg
文件 1571 2008-12-11 23:24 ROFdenoise.m
文件 82 2008-12-11 23:24 __MACOSX\._ROFdenoise.m
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