Context-based binary arithmetic coding for fine granuality scalability

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1 Scopus citations

Abstract

A context-based binary arithmetic coding to improve entropy coding of the enhancement layer for the H.26L-based fine granularity scalability (FGS) is proposed. Instead of independent bit-plane coding, we exploit correlation between various bit-planes and neighboring coefficients. For each bit-plane, we perform significant/refinement bit partition and construct contexts separately in terms of energy clustering and distribution of DCT coefficients. For the significant bit, we extend one-dimensional run-length coding to multiple dimensions and segment the significant bit-planes. For the refinement bit, we put together refinement bits exhibiting stronger correlation by energy groups and apply run-length coding distinctively. Particularly, we introduce the maximum run concept to offer better statistical adaptation. Averagely, our approach reduces the enhancement-layer bit stream by 7-8% and improves the PSNR by 0.3-0.5 dB. Moreover, our performance outperforms the JPEG-2000 for the encoding of the enhancement layer.

Original languageEnglish
Title of host publicationProceedings - 7th International Symposium on Signal Processing and Its Applications, ISSPA 2003
PublisherIEEE Computer Society
Pages105-108
Number of pages4
ISBN (Print)0780379462, 9780780379466
DOIs
StatePublished - 1 Jan 2003
Event7th International Symposium on Signal Processing and Its Applications, ISSPA 2003 - Paris, France
Duration: 1 Jul 20034 Jul 2003

Publication series

NameProceedings - 7th International Symposium on Signal Processing and Its Applications, ISSPA 2003
Volume1

Conference

Conference7th International Symposium on Signal Processing and Its Applications, ISSPA 2003
CountryFrance
CityParis
Period1/07/034/07/03

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