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Fast Intra Encoding Decisions Based on Horizontal-Vertical Progressive Gradient Accumulation for HEVC

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Digital TV and Wireless Multimedia Communication (IFTC 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 685))

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Abstract

High Efficiency Video Coding (HEVC) employs a flexible quad-tree structure for intra prediction. It enables up to 35 prediction modes with using all the possible depth levels and prediction modes to obtain the optimal CU (coding unit) and PU (prediction unit) mode. However, these characteristics bring great computational complexity. To address this issue, we propose a progressive gradient accumulation strategy for intra encoding decisions. The horizontal and vertical progressive gradient values will be obtained by adding up all the differences of every adjacent column and row. Then, the maximum optimal depth of the neighboring CU with similar vector is used for current CU early termination, and the vector direction is used for current PU mode decision. In the process of arithmetic, the accumulative values will be simplified into only calculating the difference of edge pixels. Experimental results verify that the proposed algorithm can reduce 21.82% coding time with 3.89% BDBR increasing.

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Acknowledgment

This work is supported by National Science Foundation of China under Grant No. 61271212. National High-tech R&D Program (863 Program) under Grant No. 2015AA015903. National Science Foundation of Shanghai under Grant No. 14ZR1415200.

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Correspondence to Zhenglong Yang .

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Yang, Z., Wang, G., Fan, T., Teng, G. (2017). Fast Intra Encoding Decisions Based on Horizontal-Vertical Progressive Gradient Accumulation for HEVC. In: Yang, X., Zhai, G. (eds) Digital TV and Wireless Multimedia Communication. IFTC 2016. Communications in Computer and Information Science, vol 685. Springer, Singapore. https://doi.org/10.1007/978-981-10-4211-9_25

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  • DOI: https://doi.org/10.1007/978-981-10-4211-9_25

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-4210-2

  • Online ISBN: 978-981-10-4211-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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