Revisiting Local Texture Correlation for Rate-distortion Optimized Intra Coding

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

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Author(s)

  • Junru Li
  • Li Zhang
  • Hongbin Liu
  • Jizheng Xu

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationProceedings - DCC 2020: 2020 Data Compression Conference
EditorsAli Bilgin, Michael W. Marcellin, Joan Serra-Sagrista, James A. Storer
PublisherInstitute of Electrical and Electronics Engineers
Pages273-282
Number of pages10
ISBN (Electronic)978-1-7281-6457-1
ISBN (Print)978-1-7281-6458-8
Publication statusPublished - Mar 2020

Publication series

NameData Compression Conference Proceedings
ISSN (Print)1068-0314
ISSN (Electronic)2375-0359

Conference

Title2020 Data Compression Conference (DCC 2020)
PlaceUnited States
CitySnowbird
Period24 - 27 March 2020

Abstract

In this paper, we focus on computationally modeling of the local texture correlations, in an effort to better explore the coding modes with higher priorities in the rate-distortion optimized intra coding. In particular, strong correlations and continuities of local texture with neighboring blocks have been revealed in our analysis, and empirical justifications provide us inspirations on the joint optimization of rate-distortion-complexity when angular modes become finer to adapt the local textures. We examine the philosophy with extensive experiments conducted for refining the intra full-RD list. The results show that better coding performance with on average 0.72% and 3.00% BD-Rate savings for the natural scene and screen content sequences can be achieved in AVS3 test model HPM-5.0 under all intra configuration, with negligible encoding and decoding time variations.

Research Area(s)

  • AVS3, Intra, RDO

Citation Format(s)

Revisiting Local Texture Correlation for Rate-distortion Optimized Intra Coding. / Wang, Meng; Li, Junru; Zhang, Li; Liu, Hongbin; Xu, Jizheng; Wang, Shiqi.

Proceedings - DCC 2020: 2020 Data Compression Conference. ed. / Ali Bilgin; Michael W. Marcellin; Joan Serra-Sagrista; James A. Storer. Institute of Electrical and Electronics Engineers, 2020. p. 273-282 9105869 (Data Compression Conference Proceedings).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review