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  • Research Article
  • Open Access

Facial Image Compression Based on Structured Codebooks in Overcomplete Domain

EURASIP Journal on Advances in Signal Processing20062006:069042

  • Received: 31 July 2004
  • Accepted: 27 June 2005
  • Published:


We advocate facial image compression technique in the scope of distributed source coding framework. The novelty of the proposed approach is twofold: image compression is considered from the position of source coding with side information and, contrarily to the existing scenarios where the side information is given explicitly; the side information is created based on a deterministic approximation of the local image features. We consider an image in the overcomplete transform domain as a realization of a random source with a structured codebook of symbols where each symbol represents a particular edge shape. Due to the partial availability of the side information at both encoder and decoder, we treat our problem as a modification of the Berger-Flynn-Gray problem and investigate a possible gain over the solutions when side information is either unavailable or available at the decoder. Finally, the paper presents a practical image compression algorithm for facial images based on our concept that demonstrates the superior performance in the very-low-bit-rate regime.


  • Source Code
  • Quantum Information
  • Facial Image
  • Image Compression
  • Local Image

Authors’ Affiliations

Stochastic Image Processing Group, CUI, University of Geneva, 24 rue du Général-Dufour, Geneva, 1211, Switzerland


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© Vila-Forcén et al. 2006