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Proceedings Paper

Method of ranked residuals for binary texture filtering of additive symmetric noise
Author(s): Harold G. Longbotham; Ping Yan; Alan Conrad Bovik
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Paper Abstract

Textures are degraded by Gaussian noise in the process of image acquisition. The restoration of a texture is very important for later texture analysis and classification. In this paper, the method of ranked residuals is proposed to restore binary texture which is corrupted by Gaussian noise. This method not only deletes the noise but also preserves all details of a texture. In addition, it has the property of preserving any line endings (not necessarily straight) and any boundary (concave or convex) at any orientation, edges, and corners. The main idea of ranked residual method is that it selects the windowed pixels that are closest to the windowed central value as the subset and chooses an estimator (median, mean, LMS, etc.) to estimate the central value. This allows us to adapt our choice of subsets. Therefore whatever the shape of texture looks like, the filter can preserve the texture detail and eliminate the noise at the same time. Some synthetic and real textures are used to demonstrate the properties of this filter.

Paper Details

Date Published: 28 March 1995
PDF: 11 pages
Proc. SPIE 2424, Nonlinear Image Processing VI, (28 March 1995); doi: 10.1117/12.205212
Show Author Affiliations
Harold G. Longbotham, Univ. of Texas/San Antonio and Conceptual MindWorks, Inc. (United States)
Ping Yan, Univ. of Texas/San Antonio and Conceptual MindWorks, Inc. (United States)
Alan Conrad Bovik, Univ. of Texas/Austin (United States)


Published in SPIE Proceedings Vol. 2424:
Nonlinear Image Processing VI
Edward R. Dougherty; Jaakko T. Astola; Harold G. Longbotham; Nasser M. Nasrabadi; Aggelos K. Katsaggelos, Editor(s)

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