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Phase correlation based adaptive mode decision for the H.264/AVC

Abdelazim, Abdelrahman, Mein, Stephen James, Varley, Martin Roy, Grecos, Christos and Ait-Boudaoud, Djamel (2011) Phase correlation based adaptive mode decision for the H.264/AVC. Proceedings of SPIE - The International Society for Optical Engineering, 7871. 78710O. ISSN 0277-786X

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Official URL: http://dx.doi.org/10.1117/12.873077

Abstract

The H.264 video coding standard achieves high performance compression and image quality at the expense of increased encoding complexity, due to the very refined Motion Estimation (ME) and mode decision processes. This paper focuses on decreasing the complexity of the mode selection process by effectively applying a novel fast mode decision algorithm. Firstly the phase correlation is analysed between a macroblock and its prediction obtained from the previously encoded adjacent block. Relationships are established between the correlation value and object size and also best fit motion vector. From this a novel fast mode decision and motion estimation technique has been developed utilising preprocessing frequency domain ME in order to accurately predict the best mode and the search range. We measure the correlation between a macroblock and the corresponding prediction. Based on the result we select the best mode, or limit the mode selection process to a subset of modes. Moreover the correlation result is also used to select an appropriate search range for the ME stage. Experimental results show that the proposed algorithm significantly reduces the motion estimation time whilst maintaining similar Rate Distortion performance, when compared to both the H.264/AVC Joint Model (JM) reference software and recently reported work.

Item Type: Article
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Q Science > QA Mathematics > Computer software
T Technology > T Technology (General) > Information Technology > Computer software
Divisions: School of Computing > Staff Research and Publications
Depositing User: Caoimhe Ní Mhaicín
Date Deposited: 06 Mar 2019 12:40
Last Modified: 06 Mar 2019 12:40
URI: https://norma.ncirl.ie/id/eprint/3687

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