IEEE Trans Image Process - An efficient two-phase L(1)-TV method for restoring blurred images with impulse noise.

Tópicos

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Resumo

A two-phase image restoration method based upon total variation regularization combined with an L(1)-data-fitting term for impulse noise removal and deblurring is proposed. In the first phase, suitable noise detectors are used for identifying image pixels contaminated by noise. Then, in the second phase, based upon the information on the location of noise-free pixels, images are deblurred and denoised simultaneously. For efficiency reasons, in the second phase a superlinearly convergent algorithm based upon Fenchel-duality and inexact semismooth Newton techniques is utilized for solving the associated variational problem. Numerical results prove the new method to be a significantly advance over several state-of-the-art techniques with respect to restoration capability and computational efficiency.

Resumo Limpo

twophas imag restor method base upon total variat regular combin ldatafit term impuls nois remov deblur propos first phase suitabl nois detector use identifi imag pixel contamin nois second phase base upon inform locat noisefre pixel imag deblur denois simultan effici reason second phase superlinear converg algorithm base upon fencheldu inexact semismooth newton techniqu util solv associ variat problem numer result prove new method signific advanc sever stateoftheart techniqu respect restor capabl comput effici

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