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- W2004536086 abstract "We propose an efficient algorithm to solve the generalized Total Variation (TV) functional with a non-negativity constraint. This algorithm, which does not involve the solution of a linear system, but rather multiplicative updates only, can be used to solve the denoising and deconvolution problems. The derivation of our method is straightforward once the generalized TV functional is cast as a Non-negative Quadratic Programming (NQP) problem. The proposed algorithm offers a fair computational performance to solve the ℓ <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</sup> -TV and ℓ <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>1</sup> -TV denoising and deconvolution problems and it is the fastest algorithm of which we are aware for general inverse problems involving a nontrivial forward linear operator and a non-negativity constraint." @default.
- W2004536086 created "2016-06-24" @default.
- W2004536086 creator A5077092609 @default.
- W2004536086 date "2010-09-01" @default.
- W2004536086 modified "2023-10-18" @default.
- W2004536086 title "Multiplicative updates algorithm to minimize the generalized total variation functional with a non-negativity constraint" @default.
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- W2004536086 doi "https://doi.org/10.1109/icip.2010.5654074" @default.
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