A New Alternating Minimization Algorithm for Total Variation Image Reconstruction

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Description

the code are related to the work and code of Wang et. al.:

Y. Wang, J. Yang, W. Yin and Y. Zhang, “A New Alternating Minimization Algorithm for Total Variation Image Reconstruction”, SIAM Journal on Imaging Sciences, 1(3): 248:272, 2008. and their FTVd code.

Input Parameters:

yin: Observed blurry and noisy input grayscale image.
k: convolution kernel
lambda: parameter that balances likelihood and prior term weighting
alpha: parameter between 0 and 2
yout0: if this is passed in, it is used as an initialization for the output deblurred image; if not passed in, then the input blurry image is used as the initialization

Outputs:

yout: solution

Multi-purpose optimization for facility localization with stochastic demand by evolutionary algorithm

 

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