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Proceedings Paper

Generalized and adaptive LUM smoothers for image filtering
Author(s): M. Reza Hakami; Charles G. Boncelet
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Paper Abstract

We introduce an adaptive variant of the LUM smoother. The smoother operates on a sliding window and is designed to eliminate impulsive components with minimal distortion. In any particular window, the amount of filtering is adjusted based upon the quasi range measures of dispersion. As the results of simulations indicate, in most cases, the adaptive LUM smoother outperforms its fixed counterpart. Secondly, we generalize the two-stage LUM smoother to a multilevel order statistic filter. The generalization leads to the development of some useful filters: multiple window order statistic filters and asymmetric order statistic filters. We provide a detailed analytical and quantitative analysis of the proposed filters.

Paper Details

Date Published: 1 June 1992
PDF: 11 pages
Proc. SPIE 1668, Visual Data Interpretation, (1 June 1992); doi: 10.1117/12.59665
Show Author Affiliations
M. Reza Hakami, Univ. of Delaware (United States)
Charles G. Boncelet, Univ. of Delaware (United States)

Published in SPIE Proceedings Vol. 1668:
Visual Data Interpretation
Joanna R. Alexander, Editor(s)

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