Reversible compression of a video sequence

Nasir D. Memon, Khalid Sayood

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In addition to spatial redundancies, a sequence of video images contain spectral and temporal redundancies, which standard lossless compression techniques fail to take into account. In this paper we propose and investigate lossless compression schemes for a video sequence. Prediction schemes are presented that exploit temporal correlations and spectral correlation as well as spatial correlations. These schemes are based on the notion of a scan model which we have defined in our earlier work. A scan model effectively captures the inherent structure in an image and by using optimal scan models from spectrally and temporally adjacent frames to perform prediction in the current frame provides an effective means of utilizing spectral and temporal correlations. We also present a simpler approximation to this technique that selects an appropriate predictor from a set, by making use of information in neighboring frames. Besides effective prediction techniques, we also include a simple error modeling step that takes into account prediction errors made in spectrally and/or temporally adjacent pixels in order to efficiently encode the prediction residual. Implementation results on standard test sequences indicate that significant improvements can be obtained by the proposed techniques.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
PublisherSociety of Photo-Optical Instrumentation Engineers
Number of pages12
Editionp 3
ISBN (Print)081941638X
StatePublished - 1994
EventVisual Communications and Image Processing '94 - Chicago, IL, USA
Duration: Sep 25 1994Sep 29 1994

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Numberp 3
ISSN (Print)0277-786X


OtherVisual Communications and Image Processing '94
CityChicago, IL, USA

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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