A two-stage video coding framework with both self-adaptive redundant dictionary and adaptively orthonormalized DCT basis

Yuanyi Xue, Yi Zhou, Yao Wang

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

Abstract

In this work, we propose a two-stage video coding framework, as an extension of our previous one-stage framework in [1]. The two-stage frameworks consists two different dictionaries. Specifically, the first stage directly finds the sparse representation of a block with a self-adaptive dictionary consisting of all possible inter-prediction candidates by solving an L0-norm minimization problem using orthogonal least squares (OLS), and the second stage codes the residual using altered DCT dictionary orthonormalized to the subspace spanned by the first stage atoms. The transition of the first stage and the second stage is adaptively determined based on the estimated residual reduction per bit. We further propose a complete context adaptive entropy coder to efficiently code the locations and the coefficients of chosen first stage atoms. Simulation results show that the proposed coder significantly improves the RD performance over our previous one-stage coder. More importantly, the two-stage coder, using a fixed block size and inter-prediction only, outperforms the H.264 coder (x264) and is competitive with the HEVC reference coder (HM) over a large rate range.

Original languageEnglish (US)
Title of host publication2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings
PublisherIEEE Computer Society
Pages1697-1701
Number of pages5
ISBN (Electronic)9781479983391
DOIs
StatePublished - Dec 9 2015
EventIEEE International Conference on Image Processing, ICIP 2015 - Quebec City, Canada
Duration: Sep 27 2015Sep 30 2015

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2015-December
ISSN (Print)1522-4880

Other

OtherIEEE International Conference on Image Processing, ICIP 2015
Country/TerritoryCanada
CityQuebec City
Period9/27/159/30/15

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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