Reconstruction of high-resolution image frames from a sequence of low-resolution and compressed observations

C. Andrew Segall, Rafael Molina, Aggelos K Katsaggelos, Javier Mateos

Research output: Contribution to journalArticle

11 Scopus citations

Abstract

A framework for recovering high-resolution information from a sequence of sub-sampled and compressed observations is presented. Compression schemes that describe a video sequence through a combination of motion vectors and transform coefficients are the focus (e.g. the MPEG and ITU family of standards), and we consider the influence of both the motion vectors and transform coefficients within the reconstruction algorithm. A Bayesian approach is utilized to incorporate the information, and results show a discernable improvement in resolution, as compared to standard interpolation methods.

Original languageEnglish (US)
Pages (from-to)1701-1704
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2
DOIs
StatePublished - Jan 1 2002

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Reconstruction of high-resolution image frames from a sequence of low-resolution and compressed observations'. Together they form a unique fingerprint.

  • Cite this