A bayesian approach for the estimation and transmission of regularization parameters for reducing blocking artifacts

Javier Mateos*, Aggelos K. Katsaggelos, Rafael Molina

*Corresponding author for this work

Research output: Contribution to journalArticle

33 Scopus citations

Abstract

With block-based compression approaches for both still images and sequences of images annoying blocking artifacts are exhibited, primarily at high compression ratios. They are due to the independent processing (quantization) of the block transformed values of the intensity or the displaced frame difference. In this paper, we propose the application of the hierarchical Bayesian paradigm to the reconstruction of block discrete cosine transform (BDCT) compressed images and the estimation of the required parameters. We derive expressions for the iterative evaluation of these parameters applying the evidence analysis within the hierarchical Bayesian paradigm. The proposed method allows for the combination of parameters estimated at the coder and decoder. The performance of the proposed algorithms is demonstrated experimentally.

Original languageEnglish (US)
Pages (from-to)1200-1215
Number of pages16
JournalIEEE Transactions on Image Processing
Volume9
Issue number7
DOIs
StatePublished - Jul 1 2000

Keywords

  • Bayesian models
  • Evidence analysis
  • Image coding
  • Post-processing
  • Reconstruction

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design

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