Fast intra prediction mode decision for HEVC using random forest

Zhuge Yan; Siu Yeung Cho; Sherif Welsen

doi:10.1145/3317640.3317645

Fast intra prediction mode decision for HEVC using random forest

Zhuge Yan
, Siu Yeung Cho
, Sherif Welsen

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

10 Citations (Scopus)

312 Downloads (Pure)

Abstract

In this paper, we extracted specific image features that represent CU texture, incorporate a machine learning technique, namely random forest, in HEVC intra prediction mode selection, to improve the performance of intra coding of HEVC. Compared with similar algorithms, our method extracts very specific features of image texture changes in terms of angle. Therefore the proposed method can achieve very high prediction accuracy. Having similar reduction in complexity, the proposed algorithm can gain higher video quality compared with similar algorithms. 2019 Copyright is held by the owner/author(s).

Original language	English
Title of host publication	ACM International Conference Proceeding Series
Publisher	Association for Computing Machinery
Pages	45-49
Number of pages	5
ISBN (Print)	9781450361750
DOIs	https://doi.org/10.1145/3317640.3317645
Publication status	Published - 2019
Event	2019 International Conference on Image, Video and Signal Processing, IVSP 2019 - Shanghai, China Duration: 25 Feb 2019 → 28 Feb 2019

Publication series

Name	ACM International Conference Proceeding Series
Volume	Part F147767

Conference

Conference	2019 International Conference on Image, Video and Signal Processing, IVSP 2019
Country/Territory	China
City	Shanghai
Period	25/02/19 → 28/02/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 15 Life on Land

Free Keywords

HEVC
Intra prediction
Random forest

ASJC Scopus subject areas

Software
Human-Computer Interaction
Computer Vision and Pattern Recognition
Computer Networks and Communications

Access to Document

10.1145/3317640.3317645

Fast Intra Prediction Mode_ACM

Cite this

@inproceedings{701ad895703542769b42bac33598b99c,

title = "Fast intra prediction mode decision for HEVC using random forest",

abstract = "In this paper, we extracted specific image features that represent CU texture, incorporate a machine learning technique, namely random forest, in HEVC intra prediction mode selection, to improve the performance of intra coding of HEVC. Compared with similar algorithms, our method extracts very specific features of image texture changes in terms of angle. Therefore the proposed method can achieve very high prediction accuracy. Having similar reduction in complexity, the proposed algorithm can gain higher video quality compared with similar algorithms. 2019 Copyright is held by the owner/author(s).",

keywords = "HEVC, Intra prediction, Random forest",

author = "Zhuge Yan and Cho, \{Siu Yeung\} and Sherif Welsen",

note = "Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery. All rights reserved.; 2019 International Conference on Image, Video and Signal Processing, IVSP 2019 ; Conference date: 25-02-2019 Through 28-02-2019",

year = "2019",

doi = "10.1145/3317640.3317645",

language = "English",

isbn = "9781450361750",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

pages = "45--49",

booktitle = "ACM International Conference Proceeding Series",

}

Yan, Z, Cho, SY & Welsen, S 2019, Fast intra prediction mode decision for HEVC using random forest. in ACM International Conference Proceeding Series. ACM International Conference Proceeding Series, vol. Part F147767, Association for Computing Machinery, pp. 45-49, 2019 International Conference on Image, Video and Signal Processing, IVSP 2019, Shanghai, China, 25/02/19. https://doi.org/10.1145/3317640.3317645

Fast intra prediction mode decision for HEVC using random forest. / Yan, Zhuge; Cho, Siu Yeung; Welsen, Sherif.
ACM International Conference Proceeding Series. Association for Computing Machinery, 2019. p. 45-49 (ACM International Conference Proceeding Series; Vol. Part F147767).

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Fast intra prediction mode decision for HEVC using random forest

AU - Yan, Zhuge

AU - Cho, Siu Yeung

AU - Welsen, Sherif

PY - 2019

Y1 - 2019

N2 - In this paper, we extracted specific image features that represent CU texture, incorporate a machine learning technique, namely random forest, in HEVC intra prediction mode selection, to improve the performance of intra coding of HEVC. Compared with similar algorithms, our method extracts very specific features of image texture changes in terms of angle. Therefore the proposed method can achieve very high prediction accuracy. Having similar reduction in complexity, the proposed algorithm can gain higher video quality compared with similar algorithms. 2019 Copyright is held by the owner/author(s).

AB - In this paper, we extracted specific image features that represent CU texture, incorporate a machine learning technique, namely random forest, in HEVC intra prediction mode selection, to improve the performance of intra coding of HEVC. Compared with similar algorithms, our method extracts very specific features of image texture changes in terms of angle. Therefore the proposed method can achieve very high prediction accuracy. Having similar reduction in complexity, the proposed algorithm can gain higher video quality compared with similar algorithms. 2019 Copyright is held by the owner/author(s).

KW - HEVC

KW - Intra prediction

KW - Random forest

UR - https://www.scopus.com/pages/publications/85065790450

U2 - 10.1145/3317640.3317645

DO - 10.1145/3317640.3317645

M3 - Conference contribution

AN - SCOPUS:85065790450

SN - 9781450361750

T3 - ACM International Conference Proceeding Series

SP - 45

EP - 49

BT - ACM International Conference Proceeding Series

PB - Association for Computing Machinery

T2 - 2019 International Conference on Image, Video and Signal Processing, IVSP 2019

Y2 - 25 February 2019 through 28 February 2019

ER -

Fast intra prediction mode decision for HEVC using random forest

Abstract

Publication series

Conference

UN SDGs

Free Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this