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Vector Quantization in SPIHT Image Codec

  • Rafi Mohammad
  • Christopher F. Barnes
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4319)

Abstract

The image coding algorithm “Set Partitioning in Hierarchical Trees (SPIHT)” introduced by Said and Pearlman achieved an excellent rate-distortion performance by an efficient ordering of wavelet coefficients into subsets and bit plane quantization of significant coefficients. We observe that there is high correlation among the significant coefficients in each SPIHT pass. Hence, in this paper we propose trained scalar-vector quantization (depending on a boundary threshold) of significant coefficients to exploit correlation. In each pass, the decoder reconstructs coefficients with scalar or vector quantized values rather than with bit plane quantized values. Our coding method outperforms the scalar SPIHT coding in the high bit-rate region for standard test images.

Keywords

Vector Quantization Image Code Scalar Quantization Vector Quantization Index Sorting Step 
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

  • Rafi Mohammad
    • 1
  • Christopher F. Barnes
    • 1
  1. 1.School of Electrical and Computer EngineeringGeorgia Institute of TechnologyAtlantaUSA

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