Research and application of YOLOv3-based intelligent module for remote sensing image recognition on satellites

Hua Tang; Bingxin Ye; Huajun Shi; He Wang; Tao Yu

doi:10.1117/12.2684759

21 July 2023 Research and application of YOLOv3-based intelligent module for remote sensing image recognition on satellites

Hua Tang, Bingxin Ye, Huajun Shi, He Wang, Tao Yu

Author Affiliations +

Proceedings Volume 12717, 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023); 1271714 (2023) https://doi.org/10.1117/12.2684759
Event: 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023), 2023, Wuhan, China

Abstract

With the continuous development of satellite technology, the acquisition and processing of satellite remote sensing data have become increasingly common. However, at present, satellites still use a mode of transmitting data back to the ground and utilizing ground CPU/GPU platforms for intelligent processing, which is inefficient due to the process of data transmission between the satellite and the ground. This article studies the application method and implementation of real-time remote sensing image recognition by integrating the Yulong810 on-board intelligent module on a satellite based on the YOLOv3 object detection algorithm. In response to the actual needs of satellite remote sensing image recognition, the algorithm is optimized based on the Yulong810 on-board intelligent module, which improves the recognition efficiency and reduces power consumption while ensuring the accuracy of remote sensing image recognition. By comparing with ground CPU/GPU platforms, the results show that the Yulong810 on-board intelligent module has lower power consumption and higher efficiency, and the recognition accuracy is comparable to that of ground platforms, which can completely replace ground remote sensing image detection equipment when integrated into satellites. By integrating the module into the satellite, real-time intelligent processing can be achieved in orbit, improving the efficiency of satellite remote sensing image recognition.

Citation Download Citation

Hua Tang, Bingxin Ye, Huajun Shi, He Wang, and Tao Yu "Research and application of YOLOv3-based intelligent module for remote sensing image recognition on satellites", Proc. SPIE 12717, 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023), 1271714 (21 July 2023); https://doi.org/10.1117/12.2684759

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KEYWORDS

Remote sensing

Satellites

Target detection

Detection and tracking algorithms

Image processing

Power consumption

Image transmission

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