Embedded quantizer design for low rate lossy image coding

Francesc Aulí-Llinàs, Michael W. Marcellin, Leandro Jiménez-Rodríguez, Ian Blanes, Joan Serra-Sagrista

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

4 Scopus citations


Embedded quantization is a mechanism employed by lossy image coding systems to successively refine the distortion of an image. Commonly, it is conducted through a uniform scalar dead zone quantizer (USDQ) together with a bitplane coding strategy (BPC). Although this scheme is convenient for current hardware architectures and achieves competitive coding performance, it establishes the embedded quantizer without allowing major variations. This paper studies the design of non-restricted embedded quantizers with the aim to determine a quantization scheme that provides (near-)optimal performance for the lossy compression of images at low rates. Results suggest that optimally designed quantization schemes can achieve slightly better performance than that of USDQ+BPC by employing a non-uniform quantizer that requires fewer quantization stages.

Original languageEnglish (US)
Title of host publicationProceedings - DCC 2012
Subtitle of host publication2012 Data Compression Conference
Number of pages10
StatePublished - 2012
Event2012 Data Compression Conference, DCC 2012 - Snowbird, UT, United States
Duration: Apr 10 2012Apr 12 2012

Publication series

NameData Compression Conference Proceedings
ISSN (Print)1068-0314


Other2012 Data Compression Conference, DCC 2012
Country/TerritoryUnited States
CitySnowbird, UT


  • Embedded quantization
  • JPEG2000
  • lossy image coding

ASJC Scopus subject areas

  • Computer Networks and Communications


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