CNN based optimal intra prediction mode estimation in video coding

Ryota Yokoyama, Masahiko Tahara, Masaru Takeuchi, Heming Sun, Yasutaka Matsuo, Jiro Katto

研究成果: Conference contribution

抜粋

The amount of video data is so large that efficient video compression is required for the storage and transmission. Intra prediction is one of important components in video compression. In this paper, we examine various Convolutional Neural Network (CNN) structures to estimate optimal intra prediction mode as Most Probable Modes (MPMs). Moreover, we investigate several combinations of the MPMs obtained by the CNN and MPMs derived from High Efficiency Video Coding Test Model (HM). From these experimental results, we find that using 6 MPMs from both CNN and HM with moderate number of channels or kernel size is preferred.

元の言語English
ホスト出版物のタイトル2020 IEEE International Conference on Consumer Electronics, ICCE 2020
出版者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781728151861
DOI
出版物ステータスPublished - 2020 1
イベント2020 IEEE International Conference on Consumer Electronics, ICCE 2020 - Las Vegas, United States
継続期間: 2020 1 42020 1 6

出版物シリーズ

名前Digest of Technical Papers - IEEE International Conference on Consumer Electronics
2020-January
ISSN(印刷物)0747-668X

Conference

Conference2020 IEEE International Conference on Consumer Electronics, ICCE 2020
United States
Las Vegas
期間20/1/420/1/6

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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  • これを引用

    Yokoyama, R., Tahara, M., Takeuchi, M., Sun, H., Matsuo, Y., & Katto, J. (2020). CNN based optimal intra prediction mode estimation in video coding. : 2020 IEEE International Conference on Consumer Electronics, ICCE 2020 [9043170] (Digest of Technical Papers - IEEE International Conference on Consumer Electronics; 巻数 2020-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCE46568.2020.9043170