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Smart Grid Technologies
Published in Stuart Borlase, Smart Grids, 2017
Another key benefit of VVC is that of security and reliability. As the growth of customer load outpaces the supply, the utility power delivery reserves are dwindling, making the system more susceptible to brownouts (suppressed voltage conditions) and blackouts (loss of power). VVC helps increase the available capacity of the power delivery system.
Cloud VR Service Platform Technologies
Published in Huaping Xiong, Dawei Li, Kun Huang, Mu Xu, Yin Huang, Lingling Xu, Jianfei Lai, Shengjun Qian, Cloud VR, 2020
Huaping Xiong, Dawei Li, Kun Huang, Mu Xu, Yin Huang, Lingling Xu, Jianfei Lai, Shengjun Qian
Raw video data consumes large amounts of bandwidth and storage space. Therefore, it must be compressed using standards such as the advanced video coding (AVC or H.264), high efficiency video coding (HEVC or H.265), or versatile video coding (VVC or H.266) standard (currently being developed).
Analysis of coding unit partitioning and complexity reduction at intra-prediction mode of HEVC
Published in The Imaging Science Journal, 2022
Yogita M. Vaidya, Shilpa P. Metkar
The literature survey encompasses the complete era of HEVC from its inception in 2012 to 2021. The successor of HEVC is the Versatile Video Coding standard (VVC) [20]. Many more advanced features are implemented in VVC for HD video quality [21]. In [22] L.Shen extended the idea of fast mode decision for VVC. Following the same ideas of complexity reduction our proposed hybrid approach intends to reduce the number of candidate CUs undergoing the time-consuming RDO process. In the proposed methodology, at the first step, we have categorized the CU into homogeneous and non-homogeneous based on the gradient response. Homogeneous CUs are skipped in the RDO process and the number of candidate CUs is reduced at the first level. In the second step, the early termination decision of non-homogeneous CUs is taken by the machine learning approach to further reduce the number of candidate CUs out of non-homogeneous CUs. Thus, the novelty of the algorithm is in its two-step approach of reducing the number of CUs undergoing the RD search. The proposed hybrid approach is evaluated based on the encoding time and bit rate as the evaluation metrics. The hybrid algorithm is more efficient in terms of complexity reduction than the standard HM reference model and other approaches.