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  4. A 3D HEVC Fast Mode Decision Algorithm Based on the Depth Information Guided Maximum Coding Level.
 
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A 3D HEVC Fast Mode Decision Algorithm Based on the Depth Information Guided Maximum Coding Level.

Journal
Data Compression Conference, DCC 2014, Snowbird, UT, USA, 26-28 March, 2014
Pages
413
Date Issued
2014
Author(s)
Li, Ming-Chang
Lin, Yu-Hsun
Lin, Yin-Tzu
Shen, Yun-Chung
JA-LING WU  
DOI
10.1109/DCC.2014.35
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/501888
URL
https://doi.org/10.1109/DCC.2014.35
Abstract
3D HEVC is one of the extensions of HEVC (High Efficiency Video Coding), which is the latest video coding standard developed by the Joint Collaborative Team on Video Coding (JCT-VC). The inherent high computing complexity of 3D HEVC handicaps its usage in practical applications. HEVC replaces the macroblock (MB) of H.264 with the largest coding unit (LCU), in which coding units (CUs) of sizes 64 × 64, 32 × 32, 16 × 16, or 8 × 8 pixels are used to build a coding tree unit (CTU). HEVC encoder will traverse the coding modes from the root (the coding level is 0) to the leaves (the coding level is 3) of the CTU. As a result, how to accelerate the encoding process of 3D HEVC with negligible loss of coding efficiency is a hot research topic in the field of video coding. Figure 1 shows the coding level distributions of I04 and I14, where Ikj represents the j-th frame in the k-th GOP. The POC's (picture order counts) of the two frame are P(I04) = 4 and P(I14) = 12 when GOP size is 8. From Figure 1 we observed that, in B-slices, the distributions of "optimal coding level = zero" for adjacent GOP's are almost the same. We found that the required coding level will be similar when the two CUs have similar depth values. We utilize this correlation to limit the required coding level visiting of a given CU which accelerates the encoding process. In this paper, a fast mode decision algorithm for 3D HEVC, based on the depth information related coding mode similarity, is proposed. According to the experimental results, the proposed algorithm can reduce up to 72% executing time of the overall encoding process, while the loss in coding efficiency is negligible.
Type
conference paper

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