A Fast Encoding Scheme for High Efficiency Video Coding

Author:

Barr Mohammad1ORCID

Affiliation:

1. Department of Electrical Engineering, Northern Border University, Arar, Saudi Arabia

Abstract

Background: High-Efficiency Video Coding (HEVC) is a recent video compression standard. It provides better compression performance compared to its predecessor, H.264/AVC. However, the computational complexity of the HEVC encoder is much higher than that of H.264/AVC encoder. This makes HEVC less attractive to be used in real-time applications and in devices with limited resources (e.g., low memory, low processing power, etc.). The increased computational complexity of HEVC is partly due to its use of a variable size Transform Unit (TU) selection algorithm which successively performs transform operations using transform units of different sizes before selecting the optimal transform unit size. In this paper, a fast transform unit size selection method is proposed to reduce the computational complexity of an HEVC encoder. Methods: Bayesian decision theory is used to predict the size of the TU during encoding. This is done by exploiting the TU size decisions at a previous temporal level and by modeling the relationship between the TU size and the Rate-Distortion (RD) cost values. Results: Simulation results show that the proposed method achieves a reduction of the encoding time of the latest HEVC encoder by 16.21% on average without incurring any noticeable compromise on its compression efficiency. The algorithm also reduces the number of transform operations by 44.98% on average. Conclusion: In this paper, a novel fast TU size selection scheme for HEVC is proposed. The proposed technique outperforms both the latest HEVC reference software, HM 16.0, as well as other state-of-the-art techniques in terms of time-complexity. The compression performance of the proposed technique is comparable to that of HM 16.0.

Publisher

Bentham Science Publishers Ltd.

Subject

Electrical and Electronic Engineering,Electronic, Optical and Magnetic Materials

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3