Perceptually tuned embedded zerotree image coder

Ingo Hontsch, Lina Karam, Robert J. Safranek

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations


Embedded zerotree wavelet coding (EZW), introduced by J.M. Shapiro and recently improved by A. Said and W.A. Pearlman using an algorithm based on set partitioning in hierarchical trees (SPIHT), is a computationally inexpensive image coding technique and has proven to be very effective at minimizing the mean-square error (MSE) distortion measure. However, minimizing MSE does not guarantee preservation of good perceptual qualities in the decoded image, especially at low bit rates. In this paper we propose a perceptually-tuned embedded zerotree image codec (PEZ) that introduces a perceptual weighting to the wavelet transform coefficients prior to EZW encoding. In this coder the EZW minimizes a perceptually based distortion measure instead of MSE. The perceptual weights for all subbands are computed based on the just noticeable distortion (JND) thresholds for uniform noise. The new perceptually tuned codec has the same complexity as the original EZW/SPIHT techniques and results in a comparable or superior coding performance. Coding results are presented to illustrate the performance of the new coder.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Image Processing
Place of PublicationLos Alamitos, CA, United States
PublisherIEEE Comp Soc
Number of pages4
StatePublished - 1997
EventProceedings of the 1997 International Conference on Image Processing. Part 2 (of 3) - Santa Barbara, CA, USA
Duration: Oct 26 1997Oct 29 1997


OtherProceedings of the 1997 International Conference on Image Processing. Part 2 (of 3)
CitySanta Barbara, CA, USA

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Electrical and Electronic Engineering


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