A successively refinable lossless image-coding algorithm

Ismail Avcibaş, Nasir Memon, Bülent Sankur, Khalid Sayood

Research output: Contribution to journalArticlepeer-review


We present a compression technique that provides progressive transmission as well as lossless and near-lossless compression in a single framework. The proposed technique produces a bit stream that results in a progressive, and ultimately lossless, reconstruction of an image similar to 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 decoding of each layer of the successively refinable bit stream. We formulate the image data-compression problem as one of successively refining the probability density function (pdf) estimate of each pixel. Within this framework, restricting the region of support of the estimated pdf to a fixed size interval then results in near-lossless reconstruction. We address the context-selection problem, as well as pdf-estimation methods based on context data at any pass. Experimental results for both lossless and near-lossless cases indicate that the proposed compression scheme, that innovatively combines lossless, near-lossless, and progressive coding attributes, gives competitive performance in comparison with state-of-the-art compression schemes.

Original languageEnglish (US)
Pages (from-to)445-452
Number of pages8
JournalIEEE Transactions on Communications
Issue number3
StatePublished - Mar 2005


  • Embedded bit stream
  • Image compression
  • Lossless compression
  • Near-lossless compression
  • Probability mass estimation
  • Successive refinement

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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