Image coding using wavelet transforms and entropy-constrained trellis coded quantization

  • Authors:

  • Parthasarathy Sriram;Michael W. Marcellin

  • Affiliations:

  • Department of Electrical and Computer Engineering, The University of Arizona, Tucson, AZ;Department of Electrical and Computer Engineering, The University of Arizona, Tucson, AZ

  • Venue:
  • ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: image and multidimensional signal processing - Volume V
  • Year:
  • 1993

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Abstract

The discrete wavelet transform has recently emerged as a powerful technique for decomposing images into various multi-resolution approximations. Multiresolution decomposition schemes have proven to be very effective for high-quality, low bit-rate image coding. In this work, we investigate the use of entropy-constrained trellis coded quantization for encoding the wavelet coeficients of both monochrome and color images. Excellent peak signal-to-noise ratios are obtained for encoding monochrome and color versions of the 512 × 512 "Lenna" image. Comparisons with other results from the literature reveal that the proposed wavelet coder is quite competitive.