Fast Bit Rate Estimation for Mode Decision of H.264/AVC
To achieve the highest coding efficiency, H.264/AVC uses rate-distortion optimization technique. This means that the encoder has to code the video by exhaustively trying all the mode combinations including the different intra- and inter-prediction modes. Therefore, the complexity and computation loa...
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Published in | IEEE transactions on circuits and systems for video technology Vol. 17; no. 10; pp. 1402 - 1407 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
New York, NY
IEEE
01.10.2007
Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
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Summary: | To achieve the highest coding efficiency, H.264/AVC uses rate-distortion optimization technique. This means that the encoder has to code the video by exhaustively trying all the mode combinations including the different intra- and inter-prediction modes. Therefore, the complexity and computation load of video coding in H.264/AVC increase drastically compared to any previous standards. To reduce the complexity of rate-distortion cost computation, we propose a fast bit rate estimation technique to avoid the entropy coding method during intra- and inter-mode decision of H.264/AVC. The estimation method is based on the properties of context-based variable length coding (CAVLC). The proposed rate model predicts the rate of a 4 times 4 quantized residual block using five different tokens of CAVLC. Experimental results demonstrate that the proposed estimation method reduces about 47% of total encoding time on using intra-modes only and saves about 34% of total encoding time on using both inter- and intra-modes with ignorable degradation of coding performance when the fast motion search algorithm is used. When full search motion estimation algorithm is used, the proposed algorithm reduces about 17% of total encoding time. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
ISSN: | 1051-8215 1558-2205 |
DOI: | 10.1109/TCSVT.2007.903787 |