Saving Bits Using Multi-Sensor Collaboration

被引:0
|
作者
Ji, Zhe [1 ]
Lan, Hui [1 ]
Jung, Cheolkon [1 ]
Zou, Dan [2 ]
Li, Ming [2 ]
机构
[1] Xidian Univ, Sch Elect Engn, Xian 710071, Peoples R China
[2] Guangdong OPPO Mobile Telecommun Corp, Dongguan 523860, Peoples R China
基金
中国国家自然科学基金;
关键词
Collaboration; Convolutional neural networks; Image color analysis; Image coding; Sensors; Three-dimensional displays; VIdeo coding; 3D-HEVC; convolutional neural network; multi-sensor collaboration; redundancy; video coding; VIDEO; EXTENSIONS;
D O I
10.1109/ACCESS.2023.3234917
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we propose a new video coding method that saves bits using multi-sensor collaboration. Traditional video coding methods have saved bits by removing redundancy in videos. Recently, multiple types of sensors are being deployed to many solutions and multi-sensor data have significant advantages over single sensor data. The proposed method suggests a new way of video compression that saves bits using multi-sensor collaboration. We apply multi-sensor collaboration to the 3D video coding based on color and depth sensors. Based on the correlation between color and depth images, we design two networks CNN-US and CNN-QE in the proposed video coding method to achieve up-sampling and quality enhancement, respectively. The proposed method combines CNN-US and CNN-QE with 3D-HEVC to save bits using multi-sensor collaboration. Compared with 3D-HEVC anchor, the proposed method achieves average 5.9%, 66.8%, and 71.0% BD-rate reductions for sampling factors 1, 2, and 4 on the depth videos of 3D-HEVC test dataset, respectively.
引用
收藏
页码:4869 / 4878
页数:10
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