An L1/2-norm based efficient block level rate estimation model for HEVC

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In this paper, we propose a block level rate estimation model for HEVC in discrete cosine transformation (DCT) domain, to reduce the computation burden of entropy coding in mode decision. Rather than the widely used l0 and l1-norm, the proposed model is based on the root of l1/2-norm of the quantized DCT coefficients (r-qCoeffs) which presents a higher estimation accuracy. Furthermore, to adapt to the tree partition structured coding units in HEVC, weight matrixes of r-qCoeffs are developed for different sized transform units, where each weight is a precalculated linear function of quantization parameter (QP). Benefit from the proposed model, no parameter updating is required and high accuracy can be achieved. Experimental results show that compared with the HEVC reference software, 10.68% and 5.03% encoding time can be saved in average for intra and inter prediction mode respectively, with little rate-distortion performance loss. Besides, the proposed model that possesses a concise linear form of QP is quite qualified for the rate control mode. Results show that comparable performance to constant QP encoding mode can be achieved.

Original languageEnglish
Title of host publication2015 IEEE 17th International Workshop on Multimedia Signal Processing, MMSP 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467374781
DOIs
StatePublished - 30 Nov 2015
Event17th IEEE International Workshop on Multimedia Signal Processing, MMSP 2015 - Xiamen, China
Duration: 19 Oct 201521 Oct 2015

Publication series

Name2015 IEEE 17th International Workshop on Multimedia Signal Processing, MMSP 2015

Conference

Conference17th IEEE International Workshop on Multimedia Signal Processing, MMSP 2015
Country/TerritoryChina
CityXiamen
Period19/10/1521/10/15

Keywords

  • Adaptation models
  • Computational modeling
  • Discrete cosine transforms
  • Entropy coding
  • Estimation
  • Linearity
  • Quantization (signal)

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