A Novel Video Coding Framework Using a Self-Adaptive Dictionary

Yuanyi Xue, Yao Wang

Research output: Contribution to journalArticle

Abstract

In this paper, we propose to use a self-adaptive redundant dictionary, consisting of all possible inter and intra prediction candidates, to directly represent the frame blocks in a video sequence. The self-adaptive dictionary generalizes the conventional predictive coding approach by allowing adaptive linear combinations of prediction candidates, which is solved by an rate-distortion aware L0-norm minimization problem using orthogonal least squares (OLS). To overcome the inefficiency in quantizing and coding coefficients corresponding to correlated chosen atoms, we orthonormalize the chosen atoms recursively as part of OLS process. We further propose a two-stage video coding framework, in which a second stage codes the residual from the chosen atoms using a modified discrete cosine transform (DCT) dictionary that is adaptively orthonormalized with respect to the subspace spanned by the first stage atoms. To determine the transition from the first stage to the second stage, we propose a rate-distortion (RD) aware adaptive switching algorithm. The proposed framework is further extended to accommodate variable block sizes ( 16\times 16 , 8\times 8 , and 4\times 4 ), and the partition mode is derived by a fast partition mode decision algorithm. A context-adaptive binary arithmetic entropy coder is designed to code the symbols of the proposed coding framework. The proposed coder shows competitive, and in some cases better RD performance, compared with the HEVC video coding standard for P-frames.

Original languageEnglish (US)
Article number8058496
Pages (from-to)3478-3491
Number of pages14
JournalIEEE Transactions on Circuits and Systems for Video Technology
Volume28
Issue number12
DOIs
StatePublished - Dec 2018

Keywords

  • L0-norm minimization
  • Video coding
  • rate-distortion optimization
  • sparse coding

ASJC Scopus subject areas

  • Media Technology
  • Electrical and Electronic Engineering

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