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JPEG-2000 Compressed Image Retrieval Using Partial Entropy Decoding

  • Ha-Joong Park
  • Ho-Youl Jung
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4105)

Abstract

In this paper, we propose an efficient image retrieval method that extracts features through partial entropy decoding from JPEG-2000 compressed images. Main idea of the proposed method is to exploit the context information that is generated during context-based arithmetic encoding/decoding with three bit-plane coding passes. In the framework of JPEG-2000, the context of a current coefficient is determined depending on pattern of the significance and/or sign of its neighbors. One of nineteen contexts is at least assigned to each bit of wavelet coefficients starting from MSB (most significant bit) to LSB (least significant bit). As the context contains the directional variation of the corresponding coefficient’s neighbors, it represents the local property of image. In the proposed method, the similarity of given two images is measured by the difference between their context histograms in bit-planes. Through simulations, we demonstrate that our method achieves good performance in terms of the retrieval accuracy as well as the computational complexity.

Keywords

Image Retrieval Query Image Context Modeling Retrieval Performance JPEG Compression 
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

  • Ha-Joong Park
    • 1
  • Ho-Youl Jung
    • 1
  1. 1.Dept. of Info. And Comm. Eng.University of YeungnamKorea

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