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Refinement of Near Random Access Video Coding with Weighted Finite Automata

  • German Tischler
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4094)

Abstract

Random access video compression is mostly implemented without any reduction of temporal redundancy. Standard video compression systems like MPEG (1,2 and 4) are heavily based on motion compensation, which to some extent makes random access at single frame level impossible. We present a method for near random access video compression of low-motion video that is based on the discrete cosine transform and vector quantization and refine this system using weighted finite automata while keeping the random access property and using some reduction of temporal redundancy.

Keywords

Compression Ratio Discrete Cosine Transform Random Access Image Compression Vector Quantization 
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 2006

Authors and Affiliations

  • German Tischler
    • 1
  1. 1.Lehrstuhl für Informatik IIUniversität WürzburgWürzburgGermany

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