Efficient coding unit partition strategy for HEVC intracoding

Xuebin Sun; Xiaodong Chen; Yong Xu; Yi Wang; Daoyin Yu

doi:10.1117/1.JEI.26.4.043023

28 August 2017 Efficient coding unit partition strategy for HEVC intracoding

Xuebin Sun, Xiaodong Chen, Yong Xu, Yi Wang, Daoyin Yu

Author Affiliations +

Journal of Electronic Imaging, Vol. 26, Issue 4, 043023 (August 2017). https://doi.org/10.1117/1.JEI.26.4.043023

Abstract

As the newest international video compression standard, high efficiency video coding (HEVC) achieves a higher compression ratio and better video quality, compared with the previous standard, H.264/advanced video coding. However, higher compression efficiency is obtained at the cost of extraordinary computational load, which obstructs the implementation of the HEVC encoder for real-time applications and mobile devices. Intracoding is one of the high computational stages due to the flexible coding unit (CU) sizes and high density of angular prediction modes. This paper presents an intraencoding technique to speed up the process, which is composed of an early coding tree unit (CTU) depth interval prediction and an efficient CU partition method. The encoded CU depth information in the already encoded surrounding CTUs is utilized to predict the encoding CU search depth interval of the current CTU. By analyzing the textural features of CU, an early CU splitting termination is proposed to decide whether a CU should be decomposed into four lower-dimensions CUs or not. The experimental results indicate that the proposed algorithm outperforms the reference software HM16.7 by decreasing the coding time up to 53.67% with a negligible bit rate increase of 0.52%, and peak signal-to-noise ratio losses lower 0.06 dB, respectively.

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Xuebin Sun, Xiaodong Chen, Yong Xu, Yi Wang, and Daoyin Yu "Efficient coding unit partition strategy for HEVC intracoding," Journal of Electronic Imaging 26(4), 043023 (28 August 2017). https://doi.org/10.1117/1.JEI.26.4.043023

Received: 11 April 2017; Accepted: 3 August 2017; Published: 28 August 2017

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