Fast mode selection scheme for H.264/AVC inter prediction based on statistical learning method

Authors:
Weipeng Ma;Shuyuan Yang;Li Gao;Chaoke Pei;Shefeng Yan
Affiliations:
Graduate University of Chinese Academy of Sciences and Dept. of Digital System Integration Technique, Institute of Acoustics, CAS, Beijing, China;Dept. of Digital System Integration Technique, Institute of Acoustics, CAS, Beijing, China;Dept. of Digital System Integration Technique, Institute of Acoustics, CAS, Beijing, China;Graduate University of Chinese Academy of Sciences and Dept. of Digital System Integration Technique, Institute of Acoustics, CAS, Beijing, China;Dept. of Digital System Integration Technique, Institute of Acoustics, CAS, Beijing, China
Venue:
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Year:
2009

Citing 3
Cited 1

An Efficient Fast Mode Decision Algorithm Based on Motion Cost for H.264 Inter Prediction

IITAW '08 Proceedings of the 2008 International Symposium on Intelligent Information Technology Application Workshops
Overview of the H.264/AVC video coding standard

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Rate-Distortion and Complexity Optimized Motion Estimation for H.264 Video Coding

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Fast H.264 encoding based on statistical learning

PCM'10 Proceedings of the Advances in multimedia information processing, and 11th Pacific Rim conference on Multimedia: Part II

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Abstract

H.264 adopts variable block size motion estimation and Rate-Distortion-Optimization based mode decision to improve video quality and compression ratio. These techniques have made H.264 better than other existing video coding standards. However, they are computationally intensive and time-consuming. In this paper, a fast mode selection scheme is proposed for H.264 inter prediction. Firstly, the first few frames are encoded and thresholds are acquired through a statistical learning process. Then, for the rest of frames, motion estimation and mode decision are only performed for the candidate modes which are selected with the proposed fast mode selection scheme. The proposed approach is applicable to all existing motion search algorithms. Besides, thresholds are on-line computed separately for each sequence. Results show that the total encoding time is saved by 57.2% on average with negligible video quality degradation.