Vector excitation coding technique for image data

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


We present a VQ based technique for coding image data that, like closed loop VXC, adopts a analysis by synthesis approach. We define a new type of spatial interaction model for image data, called prediction pattern, which we use along with a quantized excitation (residuals) vector, to generate an approximation of an input block of pixels. A prediction pattern is simply a k × k array with each element representing a prediction scheme from a given set of predictors. A prediction pattern captures the spatial dependencies present in an image block. Given an image, a set of prediction schemes and a codebook of prediction patterns, we encode an image by partitioning it into blocks and for each block identifying the prediction pattern from within the codebook that best models the spatial dependencies that are present in the block. Having identified this prediction pattern we then search the residual codebook for a code vector that in combination with the already chosen prediction pattern results in the synthesis of the closest approximation to the current image block. The problem is to design an optimal set of prediction schemes and an optimal codebook of prediction patterns, given an image (or class of images). We present algorithms for codebook design and give implementation results on a few standard images. Preliminary results give substantial (between 2 or 3 db) improvements over a simple implementation of full search VQ.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
Number of pages12
StatePublished - 1996
EventStill-Image Compression II - San Jose, CA, USA
Duration: Jan 30 1996Jan 31 1996

Publication series

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


OtherStill-Image Compression II
CitySan Jose, CA, 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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