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Title: Unimodal model-based inter mode decision for high efficiency video coding
Authors: Zeng, Huanqiang
Xiang, Wenjie
Chen, Jing
Cai, Canhui
Ni, Zhangkai
Ma, Kai-Kuang
Keywords: HEVC
Coding Tree Unit
DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2019
Source: Zeng, H., Xiang, W., Chen, J., Cai, C., Ni, Z., & Ma, K.-K. (2019). Unimodal model-based inter mode decision for high efficiency video coding. IEEE Access, 7, 27936-27947. doi:10.1109/ACCESS.2019.2902196
Series/Report no.: IEEE Access
Abstract: In this paper, a fast inter mode decision algorithm, called the unimodal model-based inter mode decision (UMIMD), is proposed for the latest video coding standard, the high-efficiency video coding. Through extensive simulations, it has been observed that a unimodal model (i.e., with only one global minimum value) can be established among the size of different prediction unit (PU) modes and their resulted rate-distortion (RD) costs for each quad-tree partitioned coding tree unit (CTU). To guarantee the unimodality and further search the optimal operating point over this function for each CTU, all the PU modes need to be first classified into 11 mode classes according to their sizes. These classes are then properly ordered and sequentially checked according to the class index, from small to large so that the optimal mode can be early identified by checking when the RD cost starts to arise. In addition, an effective instant SKIP mode termination scheme is developed by simply checking the SKIP mode against a pre-determined threshold to further reduce the computational complexity. The extensive simulation results have shown that the proposed UMIMD algorithm is able to individually achieve a significant reduction on computational complexity at the encoder by 61.9% and 64.2% on average while incurring only 1.7% and 2.1% increment on the total Bjontegaard delta bit rate (BDBR) for the low delay and random access test conditions, compared with the exhaustive mode decision in the HEVC. Moreover, the experimental results have further demonstrated that the proposed UMIMD algorithm outperforms multiple state-of-the-art methods.
DOI: 10.1109/ACCESS.2019.2902196
Rights: © 2019 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See for more information.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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