Cloud removal is crucial for preprocessing optical remote sensing images affected by natural cloud contamination, which is highly diverse and variable. Clouds of varying thickness often occur simultaneously, where the boundary between these layers is ambiguous and hard to quantitatively define. Consequently, advanced d...
Yu-Jun Guo, Wei He, He Huang et al.· IEEE Transactions on Geoscie...· 0 citations
Recovering hyperspectral images (HSIs) from RGB observations is a highly ill-posed problem due to severe spectral information loss. However, current methods either rely on costly paired RGB–HSI datasets that are difficult to obtain or on unpaired RGB–HSI data for spectral guidance, which increases training costs and of...
Ningjia Lv, Feiwang Yuan, Wei He et al.· IEEE Transactions on Geoscie...· 0 citations
Inspired by human visual change perception, CogVis is proposed, a cognitive memory-guided framework that reformulates OVCD as a perception-memory-verification paradigm that achieves state-of-the-art performance across all evaluated datasets.
Rapid post-disaster response requires timely, building-level information on whether structures remain intact, are damaged, or are destroyed. Post-event optical imagery, however, may be unavailable because of cloud, smoke, or darkness. The Bright Challenge evaluated all-weather building damage mapping from a submeter-re...
Hongruixuan Chen, He Huang, Haifeng Wang et al.· arXiv.org· 0 citations
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