Xuan Sun1,2,3, Pengyu Liu1,2,3,*, Xiaowei Jia4, Kebin Jia1,2,3, Shanji Chen5, Yueying Wu1,2,3
Computer Systems Science and Engineering, Vol.39, No.2, pp. 275-286, 2021, DOI:10.32604/csse.2021.015255
Abstract This paper presents an effective machine learning-based depth selection algorithm for CTU (Coding Tree Unit) in HEVC (High Efficiency Video Coding). Existing machine learning methods are limited in their ability in handling the initial depth decision of CU (Coding Unit) and selecting the proper set of input features for the depth selection model. In this paper, we first propose a new classification approach for the initial division depth prediction. In particular, we study the correlation of the texture complexity, QPs (quantization parameters) and the depth decision of the CUs to forecast the original partition depth of the current CUs. Secondly,… More >
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