Lossless and near-lossless image compression with successive refinement

I. Avcibaş, N. Memon, B. Sankur, K. Sayood

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


We present a technique that provides progressive transmission and near-lossless compression in one single framework. The proposed technique produces a bitstream that results in progressive reconstruction of the image just like what one can obtain with a reversible wavelet codec. In addition, the proposed scheme provides near-lossless reconstruction with respect to a given bound after each layer of the successively refinable bitstream is decoded. We formulate the image data compression problem as one of asking the optimal questions to determine, respectively, the value or the interval of the pixel, depending on whether one is interested in lossless or near-lossless compression. New prediction methods based on the nature of the data at a given pass are presented and links to the existing methods are explored. The trade-off between non-causal prediction and data precision is discussed within the context of successive refinement. Context selection for prediction in different passes is addressed. Finally, experimental results for both lossless and near-lossless cases are presented, which are competitive with the state-of-the-art compression schemes.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsB. Girod, C.A. Bouman, E.G. Steinbach
Number of pages12
StatePublished - 2001
EventVisual Communications and Image Processing 2001 - San Jose, CA, United States
Duration: Jan 24 2001Jan 26 2001


OtherVisual Communications and Image Processing 2001
Country/TerritoryUnited States
CitySan Jose, CA


  • Causal non-causal prediction
  • Density estimation
  • Embedded bit stream
  • Lossless compression
  • Near-lossless compression
  • Rate scalable compression
  • Successive refinement

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics


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