The aim of this paper is to analyze the behavior of the interior point (IP) approach for an image processing application that requires to solve a large scale nonlinear programming problem, such as the denoising of an image corrupted by Poisson noise. We devise two dierent IP algorithms following the two well known globalization strategies, line search and trust region, with the aim to obtain an acceptable compromise between convergence rate and computational cost per iteration. We show that the obtained algorithms can be useful for computing high accuracy solutions.

Analysis of interior point methods for edge–preserving removal of Poisson noise

BONETTINI, Silvia;RUGGIERO, Valeria
2012

Abstract

The aim of this paper is to analyze the behavior of the interior point (IP) approach for an image processing application that requires to solve a large scale nonlinear programming problem, such as the denoising of an image corrupted by Poisson noise. We devise two dierent IP algorithms following the two well known globalization strategies, line search and trust region, with the aim to obtain an acceptable compromise between convergence rate and computational cost per iteration. We show that the obtained algorithms can be useful for computing high accuracy solutions.
9788854856875
Interior point; image denoising; Poisson data
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/1746296
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