A new hyperspectral compressed sensing method for efficient satellite communications

Chia Hsiang Lin, José M. Bioucas Dias, Tzu Hsuan Lin, Yen Cheng Lin, Chi Hung Kao

研究成果: Conference contribution

摘要

Directly transmitting the huge amount of typical hyperspectral data acquired on satellite to the ground station is inefficient. This paper proposes a new compressed sensing strategy for hyperspectral imagery on spaceborne sensors systems. As the onboard computing/storage resources are limited, e.g., on CubeSat, the measurement strategy should be computationally very light. Furthermore, considering the limited communication bandwidth, a very low sampling rate is desired. Our encoder accounts for these requirements by separately recording the spatial details and the spectral information, both of which essentially require only simple averaging operators. Our measurement strategy naturally induces a reconstruction criterion that can be elegantly interpreted as a well-known fusion problem in satellite remote sensing, allowing the adoption of a convex optimization method for simple and fast decoding. Our method, termed spatial/spectral compressed encoder (SPACE), is experimentally evaluated on real hyperspectral data, showing superior efficacy in terms of both sampling rate and reconstruction accuracy.

原文English
主出版物標題2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop, SAM 2020
發行者IEEE Computer Society
ISBN(電子)9781728119465
DOIs
出版狀態Published - 2020 六月
事件11th IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2020 - Hangzhou, China
持續時間: 2020 六月 82020 六月 11

出版系列

名字Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
2020-June
ISSN(電子)2151-870X

Conference

Conference11th IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2020
國家China
城市Hangzhou
期間20-06-0820-06-11

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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