Highly accurate distortion estimation for JPEG2000 through pdf-based estimators

Francesc Aulí-Llinàs, Michael W. Marcellin, Joan Serra-Sagristà

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

Abstract

Distortion estimation techniques are often employed in bitplane coding engines to minimize the computational load, or the memory requirements, of the encoder. A common approach is to determine distortion estimators that approximate the mean squared error decreases when data are successively coded and transmitted. Such estimators usually assume that coefficients are uniformly distributed in the quantization interval. Even though this assumption simplifies estimation, it does not exactly correspond with the nature of the signal. This work introduces new distortion estimators determined through a precise approximation of the coefficient's distribution within the quantization intervals. Experimental results obtained when our estimators are used for the post-compression rate-distortion optimization process of JPEG2000 suggest that they are able to approximate distortion with very high accuracy.

Original languageEnglish (US)
Title of host publicationProceedings - 2009 Data Compression Conference, DCC 2009
Pages391-400
Number of pages10
DOIs
StatePublished - Jul 23 2009
Event2009 Data Compression Conference, DCC 2009 - Snowbird, UT, United States
Duration: Mar 16 2009Mar 18 2009

Publication series

NameProceedings - 2009 Data Compression Conference, DCC 2009

Other

Other2009 Data Compression Conference, DCC 2009
CountryUnited States
CitySnowbird, UT
Period3/16/093/18/09

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ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Software

Cite this

Aulí-Llinàs, F., Marcellin, M. W., & Serra-Sagristà, J. (2009). Highly accurate distortion estimation for JPEG2000 through pdf-based estimators. In Proceedings - 2009 Data Compression Conference, DCC 2009 (pp. 391-400). [4976483] (Proceedings - 2009 Data Compression Conference, DCC 2009). https://doi.org/10.1109/DCC.2009.20