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Floop: An efficient video coding flow for unmanned aerial vehicles

  • Yu Su (China Mobile Chengdu Institute of Research and Development) ;
  • Qianqian Cheng (China Mobile Chengdu Institute of Research and Development) ;
  • Shuijie Wang (China Mobile Chengdu Institute of Research and Development) ;
  • Jian Zhou (China Mobile Chengdu Institute of Research and Development) ;
  • Yuhe Qiu (China Mobile Chengdu Institute of Research and Development)
  • Received : 2022.03.18
  • Accepted : 2022.08.15
  • Published : 2023.08.10

Abstract

Under limited transmission conditions, many factors affect the efficiency of video transmission. During the flight of an unmanned aerial vehicle (UAV), frequent network switching often occurs, and the channel transmission condition changes rapidly, resulting in low-video transmission efficiency. This paper presents an efficient video coding flow for UAVs working in the 5G nonstandalone network and proposes two bit controllers, including time and spatial bit controllers, in the flow. When the environment fluctuates significantly, the time bit controller adjusts the depth of the recursive codec to reduce the error propagation caused by excessive network inference. The spatial bit controller combines the spatial bit mask with the channel quality multiplier to adjust the bit allocation in space to allocate resources better and improve the efficiency of information carrying. In the spatial bit controller, a flexible mini graph is proposed to compute the channel quality multiplier. In this study, two bit controllers with end-to-end codec were combined, thereby constructing an efficient video coding flow. Many experiments have been performed in various environments. Concerning the multi-scale structural similarity index and peak signal-to-noise ratio, the performance of the coding flow is close to that of H.265 in the low bits per pixel area. With an increase in bits per pixel, the saturation bottleneck of the coding flow is at the same level as that of H.264.

Keywords

Acknowledgement

We would like to thank Yuanlin Xu, Ziyang Liu, Yike Ren, and Hangyu Li and othe for UAV data collection. This work is supported by the CMLC team of China Mobile Chengdu Institute of Research and Development, Chengdu, China.

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