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3D-Gradient Guided Rate Control Model for Screen Content Video Coding

delete2023-01-01
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PRE
AI
J
Jing Chen
L
Linlin Chen
H
Huanqiang Zeng *
C
Chih‐Hsien Hsia
T
Tianlei Wang
K
Kai‐Kuang Ma
DOI:10.1109/TMM.2022.3232020delete
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摘要

摘要

En 中文
Compared with natural videos, screen content videos (SCVs) have particular features, such as fruitful sharper edges, lots of computer-generated graphics and texts, a large amount of flat areas. New tools are adopted to HEVC extensions on Screen Content Coding (HEVC-SCC), the traditional video rate control methods for natural videos are not effective for SCVs. For that, a 3D-gradient guided rate control model for SCV coding, named 3DG-RC, is proposed to allocate bitrate more efficiently serving for SCVs. By considering the particular spatial-temporal characteristics of SCVs, the spatial and temporal feature extraction scheme is developed by using 3D-gradient filter and performed on the SCV to extract the spatial and temporal features simultaneously for guiding the bit allocation. The spatial-temporal feature similarity between three original reference SCV frames and their reconstructed ones is used to estimate the encoding parameters of the current block and frame. Experimental results demonstrate that compared with the classical and state-of-the-art rate control methods for HEVC-SCC, the proposed 3DG-RC algorithm achieves significant bitrate mismatch reduction and coding efficiency improvement for HEVC-SCC. In specific, the proposed 3DG-RC model outperforms the rate control model in SCM-8.8 with over 41.33% and 37.95% BD-BR savings on average, for low delay B (LDB) and random access (RA) coding structure, respectively.
Keyword:
HEVC-SCC
rate control
spatial-temporal features
3D-gradient

期刊

IEEE Transactions on Multimedia 封面图
IEEE Transactions on Multimedia
IF:
9.7
论文数:
4.6K
被引数:
2.4W

机构

H
Hangzhou Dianzi University
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1.3W
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被引数: 7.5K
H
huaqiao university
学者数:
1.1W
论文数: 7.1K
被引数: 131
N
Nanyang Technological University
学者数:
4.9W
论文数: 4.8W
被引数: 8.1W
N
national i-lan university
学者数:
992
论文数: 1.3K
被引数: 0
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