A novel motion classification based intermode selection strategy for HEVC performance improvement

NEUROCOMPUTING

卷:173

Article

Podder, Pallab Kanti¹  Paul, Manoranjan¹  Murshed, Manzur² 

[1] Charles Sturt Univ, Sch Comp & Math, Bathurst, NSW 2795, Australia

[2] Federat Univ, Sch Informat Technol, Churchill, Vic 3842, Australia

关键词: HEVC;    Phase correlation;    Motion identification;    Motion classification;    Intermode selection;   

DOI  :  10.1016/j.neucom.2015.08.079

来源: Elsevier

【 摘 要 】

High Efficiency Video Coding (HEVC) standard adopts several new approaches to achieve higher coding efficiency (approximately 50% bit-rate reduction) compared to its predecessor H.264/AVC with same perceptual image quality. Huge computational time has also increased due to the algorithmic complexity of HEVC compared to H.264/AVC. However, it is really a demanding task to reduce the encoding time while preserving the similar quality of the video sequences. In this paper, we propose a novel efficient intermode selection technique and incorporate into HEVC framework to predict motion estimation and motion compensation modes between current and reference blocks and perform faster inter mode selection based on three dissimilar motion types in divergent video sequences. Instead of exploring and traversing all the modes exhaustively, we merely select a subset of candidate modes and the final mode from the selected subset is determined based on their lowest Lagrangian cost function. The experimental results reveal that average encoding time can be downscaled by 40% with similar rate-distortion performance compared to the exhaustive mode selection strategy in HEVC. (C) 2015 Elsevier B.V. All rights reserved.

【 授权许可】

Free