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Real-Time Compressed Sensing for Joint Hyperspectral Image Transmission and Restoration for CubeSat
April 25, 2024, 7:45 p.m. | Chih-Chung Hsu, Chih-Yu Jian, Eng-Shen Tu, Chia-Ming Lee, Guan-Lin Chen
cs.CV updates on arXiv.org arxiv.org
Abstract: This paper addresses the challenges associated with hyperspectral image (HSI) reconstruction from miniaturized satellites, which often suffer from stripe effects and are computationally resource-limited. We propose a Real-Time Compressed Sensing (RTCS) network designed to be lightweight and require only relatively few training samples for efficient and robust HSI reconstruction in the presence of the stripe effect and under noisy transmission conditions. The RTCS network features a simplified architecture that reduces the required training samples and …
abstract arxiv challenges cs.ai cs.cv eess.iv effects image network paper real-time restoration samples satellites sensing stripe training type
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