ITLApplied  Computational Mathematics Division
ACMD Seminar Series
Attractive Image NIST

SAC - Semi-adaptive, convex optimization methodology for image restoration

Kirsi Majava
Department of Mathematical Information Technology in University of Jyvaskyla

Tuesday, March 12, 2002 15:00-16:00,
Room 145, NIST North (820)
Tuesday, March 12, 2002 13:00-14:00,
Room 4550

Abstract: The aim of image restoration is to reconstruct both sharp edges and smooth subsurfaces from a given noisy image effectively. For this purpose, we describe a new methodology which is based on a semiadaptive, convex (SAC) optimization formulation. The SAC method describes basic steps to realize an image restoration algorithm with high restoration capability and decent computational efficiency, with automatic determination of free parameters. Another novel ingredient of the approach is the utilization of a suitable histogram capturing the basic characteristics and the amount of noise in a given digital image. The principal part of the algorithm is based on the fast active-set method for solving the BV-regularized image restoration problem.
Contact: A. J. Kearsley

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