DocumentCode :
1797054
Title :
Fast motion estimation for HEVC with adaptive search range decision on CPU and GPU
Author :
Sangmin Kim ; Dong-Kyu Lee ; Chae-Bong Sohn ; Seoung-Jun Oh
Author_Institution :
Dept. of Electron. Eng., Kwangwoon Univ., Seoul, South Korea
fYear :
2014
fDate :
9-13 July 2014
Firstpage :
349
Lastpage :
353
Abstract :
In this paper, we propose a fast Motion Estimation (ME) algorithm with Adaptive Search Range (ASR) decision to further accelerate the Graphics Processing Units (GPU)-based ME for High Efficiency Video Coding (HEVC). The proposed approach adaptively decides search ranges on the Central Processing Unit (CPU) and transfers them to the GPU. Then, the GPU performs ME process in parallel. The proposed approach solves the dependency problem in the Motion Vector Predictor (MVP) derivation stage by using only temporal Motion Vectors (MVs). The proposed algorithm yields the total encoding time reduction of 40.3% with negligible Rate Distortion (RD) loss of 1.2%. In terms of ME, the GPU-based ME with ASR decision provides the time reduction of 54.7% and 1446.8× speed-up on average compared to the GPU-based ME without ASR decision and the full-search ME in the reference model, respectively.
Keywords :
graphics processing units; motion estimation; search problems; video coding; CPU; GPU; HEVC; adaptive search range decision; central processing unit; encoding time reduction; graphics processing units; high efficiency video coding; motion estimation; motion vector predictor; rate distortion loss; temporal motion vector; Acceleration; Algorithm design and analysis; Classification algorithms; Encoding; Graphics processing units; Motion estimation; Video coding; GPGPU; HEVC; adaptive search range; motion estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal and Information Processing (ChinaSIP), 2014 IEEE China Summit & International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4799-5401-8
Type :
conf
DOI :
10.1109/ChinaSIP.2014.6889262
Filename :
6889262
Link To Document :
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