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Proceedings Paper

Estimation of image noise using polynomial masks
Author(s): Albert Akhriev; Alexander Bonch-Osmolovsky
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Paper Abstract

Many computer vision and image processing algorithms rely on the knowledge of the image noise variance as their input parameter. However, in practice, the distinction between noise and image features is not easy to draw. In this paper, image noise variance is estimated by a novel method employing rigorously derived polynomial masks. The method is based on the assumption that the image can be locally represented as a polynomial of the given degree and constitutes a generalization of some of previously proposed approaches.

Paper Details

Date Published: 28 May 2004
PDF: 12 pages
Proc. SPIE 5298, Image Processing: Algorithms and Systems III, (28 May 2004); doi: 10.1117/12.526513
Show Author Affiliations
Albert Akhriev, Institute of Information Technologies (Russia)
Alexander Bonch-Osmolovsky, Intelligent Security Systems, Ltd. (Russia)


Published in SPIE Proceedings Vol. 5298:
Image Processing: Algorithms and Systems III
Edward R. Dougherty; Jaakko T. Astola; Karen O. Egiazarian, Editor(s)

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