Progressive wavelet image coding based on a conditional probability model

Robert W. Buccigrossi, Eero P. Simoncelli

Research output: Contribution to journalConference articlepeer-review

Abstract

We present a wavelet image coder based on an explicit model of the conditional statistical relationships between coefficients in different subbands. In particular, we construct a parameterized model for the conditional probability of a coefficient given coefficients at a coarser scale. Sub-band coefficients are encoded one bitplane at a time using a non-adaptive arithmetic encoder. The overall ordering of bitplanes is determined by the ratio of their encoded variance to compressed size. We show rate-distortion comparisons of the coder to first and second-order theoretical entropy bounds and the EZW coder. The coder is inherently embedded, and should prove useful in applications requiring progressive transmission.

Original languageEnglish (US)
Pages (from-to)2957-2960
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume4
StatePublished - 1997
EventProceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP. Part 1 (of 5) - Munich, Ger
Duration: Apr 21 1997Apr 24 1997

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Progressive wavelet image coding based on a conditional probability model'. Together they form a unique fingerprint.

Cite this