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Proceedings Paper

Statistical techniques for noise removal from visual images
Author(s): Lloyd G. Allred; Gary E. Kelly
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Paper Abstract

The median operator has been demonstrated to be a very effective method for restoring recognizable images from very noisy image data. The power of the median operator stems from its non-algebraic formulation, which prevents erroneous data corrupting the final color computation. A principal drawback is that the median operator replaces all data, erroneous or not, the result being a net loss of information. This paper presents alternative statistical outlier techniques by which erroneous data is readily recognized, but valid data usually remains unchanged. The result is an effective noise removal algorithm with reduced loss of information.

Paper Details

Date Published: 1 July 1992
PDF: 6 pages
Proc. SPIE 1702, Hybrid Image and Signal Processing III, (1 July 1992); doi: 10.1117/12.60572
Show Author Affiliations
Lloyd G. Allred, Air Force Ogden Air Logistics Ctr. (United States)
Gary E. Kelly, Air Force Ogden Air Logistics Ctr, (United States)

Published in SPIE Proceedings Vol. 1702:
Hybrid Image and Signal Processing III
David P. Casasent; Andrew G. Tescher, Editor(s)

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