IEEE Trans Image Process - Fast nonconvex nonsmooth minimization methods for image restoration and reconstruction.

Tópicos

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Resumo

Nonconvex nonsmooth regularization has advantages over convex regularization for restoring images with neat edges. However, its practical interest used to be limited by the difficulty of the computational stage which requires a nonconvex nonsmooth minimization. In this paper, we deal with nonconvex nonsmooth minimization methods for image restoration and reconstruction. Our theoretical results show that the solution of the nonconvex nonsmooth minimization problem is composed of constant regions surrounded by closed contours and neat edges. The main goal of this paper is to develop fast minimization algorithms to solve the nonconvex nonsmooth minimization problem. Our experimental results show that the effectiveness and efficiency of the proposed algorithms.

Resumo Limpo

nonconvex nonsmooth regular advantag convex regular restor imag neat edg howev practic interest use limit difficulti comput stage requir nonconvex nonsmooth minim paper deal nonconvex nonsmooth minim method imag restor reconstruct theoret result show solut nonconvex nonsmooth minim problem compos constant region surround close contour neat edg main goal paper develop fast minim algorithm solv nonconvex nonsmooth minim problem experiment result show effect effici propos algorithm

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