Multi-channel Reconstruction of Video Sequences from Low-Resolution and Compressed Observations

  • Luis D. Alvarez
  • Rafael Molina
  • Aggelos K. Katsaggelos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2905)

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.

Keywords

Video Sequence Optical Flow Motion Vector High Resolution Image Smoothness Constraint 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Luis D. Alvarez
    • 1
  • Rafael Molina
    • 1
  • Aggelos K. Katsaggelos
    • 2
  1. 1.Departamento de Ciencias de la Computación e Inteligencia ArtificialUniversity of GranadaGranadaSpain
  2. 2.Department of Electrical and Computer EngineeringNorthwestern UniversityEvanstonUSA

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