Title

Improved Optimization of Soft Partition Weighted Sum Filters and Their Application to Image Restoration

Document Type

Article

Publication Date

4-2006

Publication Source

Applied Optics

Abstract

Soft-partition-weighted-sum (Soft-PWS) filters are a class of spatially adaptive moving-window filters for signal and image restoration. Their performance is shown to be promising. However, optimization of the Soft-PWS filters has received only limited attention. Earlier work focused on a stochastic-gradient method that is computationally prohibitive in many applications. We describe a novel radial basis function interpretation of the Soft-PWS filters and present an efficient optimization procedure. We apply the filters to the problem of noise reduction. The experimental results show that the Soft-PWS filter outperforms the standard partition-weighted-sum filter and the Wiener filter.

Inclusive pages

2697-2706

ISBN/ISSN

1559-128X

Publisher

OSA: The Optical Society

Volume

45

Issue

12

Peer Reviewed

yes