Low-complexity lossy image coding through a near-optimal general embedded quantizer

Francesc Aulí-Llinàs*, J. Lino Monteagudo-Pereira, Joan Serra-Sagristà, Joan Bartrina-Rapesta

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

3 Citations (Scopus)

Abstract

Embedded quantization is a mechanism employed by many lossy image codecs to progressively refine the distortion of a (transformed) image. Currently, the most common scheme to do so is to use a uniform scalar deadzone quantizer (USDQ) together with a bitplane coding (BPC) strategy. This scheme is convenient, but does not allow major variations. This paper uses the recently introduced general embedded quantizer (GEQ) to design a multi-stage quantization scheme that can be introduced in the core of modern image coding systems. Experimental results carried out in the framework of JPEG2000 indicate that the proposed scheme achieves same coding performance as that of USDQ+BPC while requiring fewer quantization stages, which reduces the computational costs of codecs without penalizing their performance.

Original languageAmerican English
JournalIET Conference Publications
Issue number600 CP
DOIs
Publication statusPublished - 2012

Keywords

  • embedded quantization
  • Image coding
  • JPEG2000

Fingerprint Dive into the research topics of 'Low-complexity lossy image coding through a near-optimal general embedded quantizer'. Together they form a unique fingerprint.

Cite this