Regularized dequantization for image copies compressed with different quantization parameters

Gao Yang, Ci Wang, Yap Peng Tan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

A single source image can be compressed into many different copies with different quantization parameters. An end user may have access to a few of such copies (e.g., over the Internet), but would like to obtain one that has superior quality to any available copy. We propose in this paper to improve the reconstruction quality by using regularization and refining the narrowed quantization constraint set (NQCS) from such image copies. Since the size of NQCS is generally large, we also discuss the estimation of initial images for regularization by applying proper probability models. Experimental results show that the proposed scheme can consistently improve the quality of the reconstructed images in both subjective and objective terms.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Image Processing, ICIP 2008 Proceedings
Pages3172-3175
Number of pages4
DOIs
StatePublished - 2008
Externally publishedYes
Event2008 IEEE International Conference on Image Processing, ICIP 2008 - San Diego, CA, United States
Duration: 12 Oct 200815 Oct 2008

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference2008 IEEE International Conference on Image Processing, ICIP 2008
Country/TerritoryUnited States
CitySan Diego, CA
Period12/10/0815/10/08

Keywords

  • Constraint set
  • Initial estimate
  • Multiple copies
  • Regularized dequantization

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