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Proceedings Paper

Optimal Detection Methods for the Restoration of Images Degraded by Signal Dependent Noise
Author(s): Kenneth E. Barner; Gonzalo R. Arce
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Paper Abstract

The restoration of images degraded by signal dependent noise has traditionally been approached from an estimation framework. These techniques, however, are heavily dependent on a complete and accurate statistical representation of an image field and tend to blur regions where this representation is inaccurate. In this paper we introduce restoration techniques based on optimal vector detection methods. The introduced restoration methods are derived from a Bayesian framework and reduce to a M-ary Hypothesis Test among a representative set, or codebook, of vectors. These techniques remove the signal dependent noise while retaining the structure required for accurate image representation.

Paper Details

Date Published: 1 November 1989
PDF: 10 pages
Proc. SPIE 1199, Visual Communications and Image Processing IV, (1 November 1989); doi: 10.1117/12.970024
Show Author Affiliations
Kenneth E. Barner, University of Delaware (United States)
Gonzalo R. Arce, University of Delaware (United States)

Published in SPIE Proceedings Vol. 1199:
Visual Communications and Image Processing IV
William A. Pearlman, Editor(s)

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