article

Fast intra mode decision algorithm for HEVC based on dominant edge assent distribution

Authors:

Yu LuAuthors Info & Claims

Multimedia Tools and Applications, Volume 75, Issue 4

Pages 1963 - 1981

https://doi.org/10.1007/s11042-014-2382-7

Published: 01 February 2016 Publication History

Abstract

As the latest video coding standard, high efficiency video coding (HEVC) is a successor to H.264/AVC. To improve the coding efficiency of intra coding, HEVC employs a flexible quad-tree coding block partitioning structure and 35 intra prediction modes. The optimal prediction mode is selected through rough mode decision (RMD) and rate distortion optimisation (RDO) process. Due to the huge search space of all of the possible depth levels (CU sizes) and intra prediction modes, intra coding of HEVC is a very time-consuming and complicated process, which limits the application of HEVC. In order to reduce the intra coding complexity, we propose a fast mode decision algorithm for HEVC intra prediction which is based on dominant edge assent (DEA) and its distribution. The four DEAs in the directions of degree 0, 45, 90 and 135 are computed first; then, the dominant edge is decided according to the minimum DEA. Next, a subset of prediction modes in accordance with the dominant edge is chosen for the RMD process. The rule is as follows: When the standard deviation of DEA is distinctly small, we skip the RMD process and take the direct current (DC) mode and planar modes as the candidate modes for the RDO process; when the minimum DEA is distinctly small, we select seven modes as the candidate modes for the RMD process; otherwise, we select 11 modes for the RMD process. Lastly, the prediction unit (PU) size-based number of RDO candidate modes (3 for PU size 4 ý4 and 8 ý8 and 1 for the other PU sizes) is modified according to experimental analysis. Compared with HM 9.1, Shen's proposal and da Silva's proposal, which are two state-of-the-art fast intra mode decision algorithms, the experimental results reveal that the proposed algorithm can save 36.26, 13.85 and 20.81 % coding time on average with a negligible loss of coding efficiency, respectively. p>

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Cited By

Pakdaman FAdelimanesh MHashemi M(2022)BLINC: lightweight bimodal learning for low-complexity VVC intra-codingJournal of Real-Time Image Processing10.1007/s11554-022-01223-119:4(791-807)Online publication date: 1-Aug-2022
https://dl.acm.org/doi/10.1007/s11554-022-01223-1
Wang JJi BWang HCheng L(2021)Prediction mode grouping and coding bits grouping based on texture complexity for Fast HEVC intra-codingJournal of Real-Time Image Processing10.1007/s11554-020-01034-218:3(839-856)Online publication date: 1-Jun-2021
https://dl.acm.org/doi/10.1007/s11554-020-01034-2
Najafabadi NRamezanpour M(2020)Mass center direction-based decision method for intraprediction in HEVC standardJournal of Real-Time Image Processing10.1007/s11554-019-00864-z17:5(1153-1168)Online publication date: 1-Oct-2020
https://dl.acm.org/doi/10.1007/s11554-019-00864-z
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Published In

cover image Multimedia Tools and Applications

Multimedia Tools and Applications Volume 75, Issue 4

February 2016

648 pages

ISSN:1380-7501

Issue’s Table of Contents

Copyright © Copyright © 2016 Springer Science+Business Media New York.

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 February 2016

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Cited By

Pakdaman FAdelimanesh MHashemi M(2022)BLINC: lightweight bimodal learning for low-complexity VVC intra-codingJournal of Real-Time Image Processing10.1007/s11554-022-01223-119:4(791-807)Online publication date: 1-Aug-2022
https://dl.acm.org/doi/10.1007/s11554-022-01223-1
Wang JJi BWang HCheng L(2021)Prediction mode grouping and coding bits grouping based on texture complexity for Fast HEVC intra-codingJournal of Real-Time Image Processing10.1007/s11554-020-01034-218:3(839-856)Online publication date: 1-Jun-2021
https://dl.acm.org/doi/10.1007/s11554-020-01034-2
Najafabadi NRamezanpour M(2020)Mass center direction-based decision method for intraprediction in HEVC standardJournal of Real-Time Image Processing10.1007/s11554-019-00864-z17:5(1153-1168)Online publication date: 1-Oct-2020
https://dl.acm.org/doi/10.1007/s11554-019-00864-z
Shabanam SUdupi VSubudhi B(2020)An efficient framework for increasing image quality using DRN Bi-layer enfolded compressorMultimedia Tools and Applications10.1007/s11042-019-08227-379:17-18(12401-12426)Online publication date: 1-May-2020
https://dl.acm.org/doi/10.1007/s11042-019-08227-3
Nair PRao KNair MThampi SEl-Alfy E(2019)A machine learning approach for fast mode decision in HEVC intra prediction based on statistical featuresJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-16992136:3(2095-2106)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.3233/JIFS-169921
Hosseini EPakdaman FHashemi MGhanbari M(2019)A computationally scalable fast intra coding scheme for HEVC video encoderMultimedia Tools and Applications10.1007/s11042-018-6713-y78:9(11607-11630)Online publication date: 1-May-2019
https://dl.acm.org/doi/10.1007/s11042-018-6713-y
Tian TWang H(2018)Large-scale video compressionFrontiers of Computer Science: Selected Publications from Chinese Universities10.1007/s11704-018-7304-912:5(825-839)Online publication date: 1-Oct-2018
https://dl.acm.org/doi/10.1007/s11704-018-7304-9
Yao YJia TLi XLu Y(2018)A fast DEA-based intra-coding algorithm for HEVCMultimedia Tools and Applications10.1007/s11042-017-4372-z77:2(1861-1881)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1007/s11042-017-4372-z
Antony AG S(2018)Selective intra prediction in HEVC planar and angular modes for efficient near-lossless video compressionMultimedia Tools and Applications10.1007/s11042-016-4309-y77:1(1093-1113)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1007/s11042-016-4309-y
Antony AG S(2017)HEVC-based lossless intra coding for efficient still image compressionMultimedia Tools and Applications10.1007/s11042-015-3138-876:2(1639-1658)Online publication date: 1-Jan-2017
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