How to optimize a function ?

Hi, i'm running a denoising algorithm on an image which is 3D image and i'm trying to implement some equations and i need help here's my code:
close all Bands =191; %no of bands
SIZE = [280,307 ,191]; %WxHxBands
lam = 0.063; B=12; X0 = multibandread('dc.tif', SIZE, 'int16',1252*2, 'bsq', 'ieee-le');
%%% Add noise (zero-mean Guassian &Salt and pepper ) % show original and noisy images
std_n=40; var_noise=std_n^2; % Gaussian noise standard deviation reduced_pw = 1.5*var_noise; % power to reduce in first phase %sig_w = 5; ws=4*sig_w+1; std_n=sqrt(var(X0(:))); Xn = randn(size(X0))*std_n; %noise
X = X0 + Xn;
figure;imagesc(abs((squeeze(X0(:,:,[50,35,30]))/max(X0(:))))); title('Original Image');
figure; imagesc(abs((squeeze(X(:,:,[50,35,30]))/max(X(:))))); title('Noisy Image ');%plotting noisy
[Gx,Gy,Gz] = gradient(X);
Rcub = sqrt((Gx.^2) + (Gy.^2) + ((Gz.^2) .*B));
------------------------------------------------------------------- now what i need to implement is this constrained least squares problem and then optimize it here's the equation :
x = argmin=||g-u||.^2+(lambda.*Rcub)
g is the observed noisy image
u is the clean image
Any help would be very appreciated Thanks

Réponses (1)

Alan Weiss
Alan Weiss le 12 Avr 2013

0 votes

Maybe a documentation example is relevant.
Alan Weiss
MATLAB mathematical toolbox documentation

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