Multiplicative updates algorithm to minimize the generalized Total Variation functional with a non-negativity constraint

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6 Citas (Scopus)

Resumen

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 ℓ2-TV and ℓ1-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.

Idioma originalInglés
Título de la publicación alojada2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
Páginas2509-2512
Número de páginas4
DOI
EstadoPublicada - 2010
Evento2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong
Duración: 26 set. 201029 set. 2010

Serie de la publicación

NombreProceedings - International Conference on Image Processing, ICIP
ISSN (versión impresa)1522-4880

Conferencia

Conferencia2010 17th IEEE International Conference on Image Processing, ICIP 2010
País/TerritorioHong Kong
CiudadHong Kong
Período26/09/1029/09/10

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