Multi-channel reconstruction of video sequences from low-resolution and compressed observations

Luis D. Alvarez*, Rafael Molina, Aggelos K. Katsaggelos

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Scopus citations

Abstract

A framework for recovering high-resolution video sequences from sub-sampled and compressed observations is presented. Compression schemes that describe a video sequence through a combination of motion vectors and transform coefficients, e.g. the MPEG and ITU family of standards, are the focus of this paper. A multichannel Bayesian approach is used to incorporate both the motion vectors and transform coefficients in it. Results show a discernable improvement in resolution in the whole sequence, as compared to standard interpolation methods.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsAlberto Sanfeliu, Jose Ruiz-Shulcloper
PublisherSpringer Verlag
Pages46-53
Number of pages8
ISBN (Print)354020590X, 9783540205906
DOIs
StatePublished - 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2905
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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