Fast Intra Coding of High Dynamic Range Videos in SHVC

Fu, Guoliang; Shen, Liquan; Yang, Hao; Hu, Xiangyu; An, Ping

doi:10.1109/lsp.2018.2867895

Cited by 12 publications

(2 citation statements)

References 19 publications

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“…[ 29 ] introduced a spatial feature method to accelerate the binary tree partition of CU. In [ 30 ], the depth information of adjacent CUs was used to determine the depth of the current CU partition. The position of reference pixels was utilized in [ 31 ] to minimize the coding complexity of the Intra Subpartition (ISP) tool.…”

Section: Related Workmentioning

confidence: 99%

Low-Complexity Multiple Transform Selection Combining Multi-Type Tree Partition Algorithm for Versatile Video Coding

Xiong

Yang

et al. 2022

Sensors

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Despite the fact that Versatile Video Coding (VVC) achieves a superior coding performance to High-Efficiency Video Coding (HEVC), it takes a lot of time to encode video sequences due to the high computational complexity of the tools. Among these tools, Multiple Transform Selection (MTS) require the best of several transforms to be obtained using the Rate-Distortion Optimization (RDO) process, which increases the time spent video encoding, meaning that VVC is not suited to real-time sensor application networks. In this paper, a low-complexity multiple transform selection, combined with the multi-type tree partition algorithm, is proposed to address the above issue. First, to skip the MTS process, we introduce a method to estimate the Rate-Distortion (RD) cost of the last Coding Unit (CU) based on the relationship between the RD costs of transform candidates and the correlation between Sub-Coding Units’ (sub-CUs’) information entropy under binary splitting. When the sum of the RD costs of sub-CUs is greater than or equal to their parent CU, the RD checking of MTS will be skipped. Second, we make full use of the coding information of neighboring CUs to terminate MTS early. The experimental results show that, compared with the VVC, the proposed method achieves a 26.40% reduction in time, with a 0.13% increase in Bjøontegaard Delta Bitrate (BDBR).

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Section: Related Workmentioning

confidence: 99%

Low-Complexity Multiple Transform Selection Combining Multi-Type Tree Partition Algorithm for Versatile Video Coding

Xiong

Yang

et al. 2022

Sensors

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“…To date, the predominant complexity optimization methods are to predict the necessary split modes by data-driven approaches [8], [9], [10], [11], [12] and statistical approaches [13], [14], [15], [16], [17]. For data-driven approaches, Yang et al [9] proposed a learning-based fast CU partition approach for intra-prediction.…”

Section: Introductionmentioning

confidence: 99%

SSIM-Variation-Based Complexity Optimization for Versatile Video Coding

Lin¹,

Lin²,

Zhang³

et al. 2022

Preprint

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To date, Versatile Video Coding (VVC) has a more magnificent overall performance than High Efficiency Video Coding (HEVC). The Quadtree with Nested Multi-Type Tree (QTMT) coding block structure can substantially enhance video coding quality in VVC. However, the coding gain also leads to a greater coding complexity. Therefore, this letter proposes a Fast Decision Scheme Based on Structural Similarity Index Metric Variation (FDS-SSIMV) to solve this problem. Firstly, the Structural Similarity Index Metric Variation (SSIMV) characteristic among the sub coding units of the spit mode is illustrated. Next, to evaluate the SSIMV value, SSIMV measure strategies are designed for different split modes in this letter. Then, the desired split modes are selected by the SSIMV values. Experimental results show that the proposed method achieves 64.74% average encoding Time Saving (TS) with a 2.79% Bjøntegaard Delta Bit Rate (BDBR), outperforming the benchmarks.

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