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Quantization Parameter Cascading for Surveillance Video Coding Considering All Inter Reference Frames

delete2021-01-01
delete14
PRE
AI
Y
Yanchao Gong
杨楷芳 cover
杨楷芳 (Kaifang Yang) *
刘莹 (Ying Liu)
K
K.P. Lim
N
Nam Ling
H
Hong Ren Wu
DOI:10.1109/TIP.2021.3087413delete
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Abstract

Abstract

En 中文
Video surveillance and its applications have become increasingly ubiquitous in modern daily life. In video surveillance system, video coding as a critical enabling technology determines the effective transmission and storage of surveillance videos. In order to meet the real-time or time-critical transmission requirements of video surveillance systems, the low-delay (LD) configuration of the advanced high efficiency video coding (HEVC) standard is usually used to encode surveillance videos. The coding efficiency of the LD configuration is closely related to the quantization parameter (QP) cascading technique which selects or determines the QPs for encoding. However, the quantization parameter cascading (QPC) technique currently adopted for the LD configuration in HEVC test model (i.e., HM) is not optimized since it has not taken full account of the reference dependency in coding. In this paper, an efficient QPC technique for surveillance video coding, referred to as QPC-SV, is proposed, considering all inter reference frames under the LD configuration. Experimental results demonstrate the efficacy of the proposed QPC-SV. Compared with the default configuration of QPC in the HM, the QPC-SV achieves significant rate-distortion performance gain with average BD-rates of -9.35% and -9.76% for the LDP and LDB configurations, respectively.
Keywords:
Encoding
Image coding
Quantization (signal)
Video surveillance
High efficiency video coding
Adaptation models
Streaming media
Video surveillance
quantization parameter cascading
low-delay configuration
inter-frame reference dependency
HEVC
VVC
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Journal

IEEE Transactions on Image Processing cover
IEEE Transactions on Image Processing
IF:
13.7
Papers:
1.0W
Citations:
8.4W

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S
Santa Clara University
Scholars:
1.2K
Papers: 1.2K
Citations: 1.7K