Updating preconditioners for nonlinear deblurring and denoising image restoration

• Autores: Daniele Bertaccini, Fiorella Sgallari
• Localización: Applied numerical mathematics, ISSN-e 0168-9274, Vol. 60, Nº. 10, 2010, págs. 994-1006
• Idioma: inglés
• DOI: 10.1016/j.apnum.2010.06.004
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• Resumen

  • Image restoration is the recovery of images that have been degraded by blur and noise. Nonlinear degenerate diffusion partial differential equation models for image restoration require often the solution of a challenging discrete problem. We consider solving the related discrete models in the time-scale steps by Krylov iterative solvers accelerated by updating a preconditioner based on incomplete factorizations which presents a global computational cost slightly more than linear in the number of the image pixels. We demonstrate the efficiency of the strategy by denoising and deblurring some images with a generalized Alvarez�Lions�Morel-like partial differential equation model discretized by a semi implicit complementary volume scheme.