2026-03-12T13:06:35Z https://tokushima-u.repo.nii.ac.jp/oai

oai:tokushima-u.repo.nii.ac.jp:02010615 2025-04-28T05:09:20Z 1713853213384:1713853295607

Saliency-Enabled Coding Unit Partitioning and Quantization Control for Versatile Video Coding Li, Wei Jiang, Xiantao Jin, Jiayuan 10380130 宋, 天 ソウ, テン Song, Tian 宋 ソウ Song 天 テン Tian Yu, Fei Richard open access This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). VVC saliency map full convolutional network coding unit partitioning bitrate reduction The latest video coding standard, versatile video coding (VVC), has greatly improved coding efficiency over its predecessor standard high efficiency video coding (HEVC), but at the expense of sharply increased complexity. In the context of perceptual video coding (PVC), the visual saliency model that utilizes the characteristics of the human visual system to improve coding efficiency has become a reliable method due to advances in computer performance and visual algorithms. In this paper, a novel VVC optimization scheme compliant PVC framework is proposed, which consists of fast coding unit (CU) partition algorithm and quantization control algorithm. Firstly, based on the visual saliency model, we proposed a fast CU division scheme, including the redetermination of the CU division depth by calculating Scharr operator and variance, as well as the executive decision for intra sub-partitions (ISP), to reduce the coding complexity. Secondly, a quantization control algorithm is proposed by adjusting the quantization parameter based on multi-level classification of saliency values at the CU level to reduce the bitrate. In comparison with the reference model, experimental results indicate that the proposed method can reduce about 47.19% computational complexity and achieve a bitrate saving of 3.68% on average. Meanwhile, the proposed algorithm has reasonable peak signal-to-noise ratio losses and nearly the same subjective perceptual quality. MDPI 2022-08-19 eng journal article VoR 390590 https://tokushima-u.repo.nii.ac.jp/records/2010615 https://doi.org/10.3390/info13080394 10.3390/info13080394 20782489 Information 13 8 394 https://tokushima-u.repo.nii.ac.jp/record/2010615/files/info_13_8_394.pdf application/pdf 3.2 MB 2023-02-01