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Fast 3D-HEVC inter mode decision algorithm based on the texture correlation of viewpoints

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Abstract

To reduce the computational complexity of 3D-HEVC, a fast inter mode decision algorithm based on texture correlation of adjacent viewpoints is proposed (FMD_inter). By studying the statistical probability of inter prediction mode distributions in 3D-HEVC coding scheme, the mode of dependent view is highly correlated with the base one, which enables the early mode decision. Moreover, by analyzing the relationship between video texture and the inter prediction mode, selectively skip checking symmetric motion partition (SMP) mode and asymmetric motion partition (AMP) mode according to the texture features of coding unit is reasonable. The proposed algorithm is able to achieve a reduction of computational complexity by 18.71% on average, while maintaining the coding efficiency. The subjective quality of the synthesized views also shows the effectiveness of the algorithm.

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Acknowledgements

This work was partially supported by National Natural Science Foundation of China (Grant Nos. 61802136 and 61871434), Natural Science Foundation of Fujian Province (Grant Nos. 2017 J05103 and 2016 J01308), Fujian-100 Talented People Program, High-level Talent Innovation Program of Quanzhou City (Grant No. 2017G027), Promotion Program for Young and Middle-aged Teacher in Science and Technology Research of Huaqiao University (Grant No. ZQN-YX403), High-Level Talent Project Foundation of Huaqiao University (Grant Nos. 16BS709, 14BS201 and 14BS204).

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Authors and Affiliations

  1. School of Information Science and Enginnering, Huaqiao University, Xiamen, China

    Jing Chen, Bohan Wang, Jie Liao & Canhui Cai

  2. Xiamen Key Laboratory of Mobile Multimedia Communications, Xiamen, China

    Jing Chen, Bohan Wang, Jie Liao & Canhui Cai

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  1. Jing Chen
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  2. Bohan Wang
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  3. Jie Liao
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  4. Canhui Cai
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Correspondence to Jing Chen.

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Chen, J., Wang, B., Liao, J. et al. Fast 3D-HEVC inter mode decision algorithm based on the texture correlation of viewpoints. Multimed Tools Appl 78, 29291–29305 (2019). https://doi.org/10.1007/s11042-018-6832-5

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