Vector Quantization with Zerotree Significance Map for Wavelet Image Coding

  • Authors:

  • Sharon M. Perlmutter;Keren O. Perlmutter;Pamela C. Cosman

  • Affiliations:

  • -;-;-

  • Venue:
  • ASILOMAR '95 Proceedings of the 29th Asilomar Conference on Signals, Systems and Computers (2-Volume Set)
  • Year:
  • 1995

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Abstract

Variable-rate tree-structured vector quantization is applied to the coefficients obtained from an orthogonal wavelet decomposition. The set of vectors from different levels of the decomposition that correspond to the same orientation and spatial location are examined in various "zerotree'' groups to determine the different bit rates and distortions achievable for the set. The decision not to code certain groups of vectors is based upon choosing the desired distortion/rate tradeoff from among the possibilities. Side information is sent to the decoder to inform it of the sequence of decisions. The resulting bit stream is entropy coded. Results of this method on the test image "Lena'' yielded a PSNR of 30.16 dB at 0.148 bpp.