Communication theoretic image restoration for binary-valued imagery

Mark A. Neifeld, Ruozhong Xuan, Michael W. Marcellin

Research output: Contribution to journalArticlepeer-review

23 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)269-276
Number of pages8
JournalApplied optics
Issue number2
StatePublished - Jan 10 2000

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering (miscellaneous)
  • Electrical and Electronic Engineering


Dive into the research topics of 'Communication theoretic image restoration for binary-valued imagery'. Together they form a unique fingerprint.

Cite this