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Applied Optics

Applied Optics


  • Vol. 39, Iss. 2 — Jan. 10, 2000
  • pp: 269–276

Communication theoretic image restoration for binary-valued imagery

Mark A. Neifeld, Ruozhong Xuan, and Michael W. Marcellin  »View Author Affiliations

Applied Optics, Vol. 39, Issue 2, pp. 269-276 (2000)

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We present a new image-restoration algorithm for binary-valued imagery. A trellis-based search method is described that exploits the finite alphabet of the target imagery. This algorithm seeks the maximum-likelihood solution to the image-restoration problem and is motivated by the Viterbi algorithm for traditional binary data detection in the presence of intersymbol interference and noise. We describe a blockwise method to restore two-dimensional imagery on a row-by-row basis and in which a priori knowledge of image pixel correlation structure can be included through a modification to the trellis transition probabilities. The performance of the new Viterbi-based algorithm is shown to be superior to Wiener filtering in terms of both bit error rate and visual quality. Algorithmic choices related to trellis state configuration, complexity reduction, and transition probability selection are investigated, and various trade-offs are discussed.

© 2000 Optical Society of America

OCIS Codes
(100.3020) Image processing : Image reconstruction-restoration
(100.3190) Image processing : Inverse problems
(100.6640) Image processing : Superresolution

Original Manuscript: April 19, 1999
Revised Manuscript: October 20, 1999
Published: January 10, 2000

Mark A. Neifeld, Ruozhong Xuan, and Michael W. Marcellin, "Communication theoretic image restoration for binary-valued imagery," Appl. Opt. 39, 269-276 (2000)

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