Image indexing using wavelet vector quantization

Fayez M. Idris, Sethuraman Panchanathan

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

18 Scopus citations

Abstract

In this paper, we propose a new technique based on wavelet vector quantization for the storage and retrieval of compressed images. Here, the images are first decomposed using wavelet transform followed by vector quantization of the transform coefficients. We note that similar images map to similar labels. Hence, the labels corresponding to an image constitute a feature vector which is used as an index to store and retrieve the image. In addition, the lowest resolution subimages resulting from the wavelet decomposition serve as visual icons for browsing purposes. The proposed technique provide fast access to the compressed images in the database has a lower cost for computing and storing the indices compared to other techniques reported in the literature.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsC.-C.J. Kuo
Pages269-275
Number of pages7
StatePublished - Dec 1 1995
Externally publishedYes
EventDigital Image Storage and Archiving Systems - Philadelphia, PA, USA
Duration: Oct 25 1995Oct 26 1995

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume2606
ISSN (Print)0277-786X

Other

OtherDigital Image Storage and Archiving Systems
CityPhiladelphia, PA, USA
Period10/25/9510/26/95

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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  • Cite this

    Idris, F. M., & Panchanathan, S. (1995). Image indexing using wavelet vector quantization. In C-CJ. Kuo (Ed.), Proceedings of SPIE - The International Society for Optical Engineering (pp. 269-275). (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 2606).