Parameter estimation in regularized reconstruction of BDCT compressed images for reducing blocking artifacts

Javier Mateos*, Aggelos K. Katsaggelos, Rafael Molina

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

High compression ratios for both still images and sequences of images are usually achieved by discarding information represented by block discrete cosine transform (BDCT) coefficients which is considered unimportant. This compression procedure yields images that exhibit annoying block artifacts. In this paper we examine the reconstruction of BDCT compressed images which results in the removal of the blocking artifact. The method we propose for the reconstruction of such images, is based on a hierarchical Bayesian approach. With such an approach image and degradation models are required. In addition, unknown hyperparameters, usually the noise and image variances, have to be estimated in advanced or simultaneously with the reconstructed image. We show how to introduce knowledge about these parameters into the reconstruction procedure. The proposed algorithm is tested experimentally.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
Pages70-81
Number of pages12
Volume2952
StatePublished - 1996
EventDigital Compression Technologies and Systems for Video Communications - Berlin, Ger
Duration: Oct 7 1996Oct 7 1996

Other

OtherDigital Compression Technologies and Systems for Video Communications
CityBerlin, Ger
Period10/7/9610/7/96

ASJC Scopus subject areas

  • Engineering(all)
  • Applied Mathematics
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics

Fingerprint Dive into the research topics of 'Parameter estimation in regularized reconstruction of BDCT compressed images for reducing blocking artifacts'. Together they form a unique fingerprint.

Cite this