📄 fpdepyou.htm
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<BODY><PRE>% Automatic noise removal using You method
% fourth order PDE
% Author Jeny
% Ref :Yu-Li You, M. Kaveh, "Fourth Order Partial Differential Equations for Noise Removal,
% IEEE Trans. Image Processing, vol. 9, no. 10, pp 1723-1730, October 2000]
% Method : du/dt = - del^2[c(del^2(u))del^u]
% where u is the noisy input image.
function [frth]=fpdepyou(I,T)
% I = Noisy Image
% T - Threshold , Based on the threshold you will get scale sapce images. At a particular
% value of T you will gwt the converged image.
[x y z]=size(I);
I=double(I);
dt=0.9; % Time step
I1=I;
I2=I;
t=1;
k=0.5;
for t=1:T
[Ix,Iy]=gradient(I1);
[Ixx,Iyt]=gradient(Ix);
[Ixt,Iyy]=gradient(Iy);
c=1./(1.+sqrt(Ixx.^2+Iyy.^2)+0.0000001);
[div1,divt1]=gradient(c.*Ixx);
[divt2,div2]=gradient(c.*Iyy);
[div11,divt3]=gradient(div1);
[divt4,div22]=gradient(div2);
div=div11+div22;
I2=I1-(dt.*div);
I1=I2;
end;
frth=uint8(I1); % Converting to 8 bit image
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