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Proceedings Paper

Anisotropic filtering with nonlinear structure tensors
Author(s): Carlos-Alberto Castaño-Moraga; Juan Ruiz-Alzola
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Paper Abstract

We present an anisotropic filtering scheme which uses a nonlinear version of the local structure tensor to dynamically adapt the shape of the neighborhood used to perform the estimation. In this way, only the samples along the orthogonal direction to that of maximum signal variation are chosen to estimate the value at the current position, which helps to better preserve boundaries and structure information. This idea sets the basis of an anisotropic filtering framework which can be applied for different kinds of linear filters, such as Wiener or LMMSE, among others. In this paper, we describe the underlying idea using anisotropic gaussian filtering which allows us, at the same time, to study the influence of nonlinear structure tensors in filtering schemes, as we compare the performance to that obtained with classical definitions of the structure tensor.

Paper Details

Date Published: 16 February 2006
PDF: 9 pages
Proc. SPIE 6064, Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning, 60640O (16 February 2006); doi: 10.1117/12.642918
Show Author Affiliations
Carlos-Alberto Castaño-Moraga, Univ. de Las Palmas de Gran Canaria (Spain)
Juan Ruiz-Alzola, Univ. de Las Palmas de Gran Canaria (Spain)

Published in SPIE Proceedings Vol. 6064:
Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning
Nasser M. Nasrabadi; Edward R. Dougherty; Jaakko T. Astola; Syed A. Rizvi; Karen O. Egiazarian, Editor(s)

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