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Proceedings Paper

Progressive indexing, retrieval, and transmission of wavelet-compressed image database
Author(s): Kai-Chieh Liang; C.-C. Jay Kuo
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Paper Abstract

A complete wavelet-based image storage and indexing system for progressive coding, indexing, retrieval, and transmission of images over the network is proposed in this research. New wavelet domain features which include subband significance, decomposition structure, luminance and chrominance histograms, and the significance map of the lowest frequency channel are used to achieve content-based indexing and retrieval. The proposed indexing features take into account of the color, brightness, texture, frequency, and spatial information of a given query image. All features can be naturally extracted as a byproduct during the image compression stage with wavelets. Since coding and indexing are integrated in an unified framework in the proposed system, the database management is greatly simplified. Extensive experimental results are given to demonstrate the retrieval performance of the new approach.

Paper Details

Date Published: 30 October 1997
PDF: 10 pages
Proc. SPIE 3169, Wavelet Applications in Signal and Image Processing V, (30 October 1997); doi: 10.1117/12.292792
Show Author Affiliations
Kai-Chieh Liang, Univ. of Southern California (United States)
C.-C. Jay Kuo, Univ. of Southern California (United States)

Published in SPIE Proceedings Vol. 3169:
Wavelet Applications in Signal and Image Processing V
Akram Aldroubi; Andrew F. Laine; Michael A. Unser, Editor(s)

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