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1 November 1989 Optimal Detection Methods for the Restoration of Images Degraded by Signal Dependent Noise
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Proceedings Volume 1199, Visual Communications and Image Processing IV; (1989) https://doi.org/10.1117/12.970024
Event: 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, 1989, Philadelphia, PA, United States
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.
© (1989) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kenneth E. Barner and Gonzalo R. Arce "Optimal Detection Methods for the Restoration of Images Degraded by Signal Dependent Noise", Proc. SPIE 1199, Visual Communications and Image Processing IV, (1 November 1989); https://doi.org/10.1117/12.970024
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