通过融合SAR和邻近光学遥感图像的特征,一种新的云去除方法
Yuyao Wang1,2,3, Jiehai Cheng1,2
1School of Surveying & Land Information Engineering, Henan Polytechnic University, Jiaozuo, China.
PloS one
|September 23, 2025
概括
这项研究引入了一种用于光学遥感图像的新云去除技术,该技术结合了合成孔径雷达 (SAR) 和光学数据. 该方法有效地恢复图像质量,增强空间和光谱细节.
科学领域:
- 地球观测 地球观测
- 地理空间科学 地理空间科学
- 遥感技术 遥感技术 遥感技术
背景情况:
- 云层严重降低光学遥感图像质量,特别是在具有挑战性的山区.
- 现有的移除云的方法往往难以保持空间细节和光谱一致性.
研究的目的:
- 为光学遥感图像开发一种有效的云移除方法.
- 提高无云光学遥感数据的准确性和质量.
主要方法:
- 一种新的粗细云去除方法,集成合成孔径雷达 (SAR) 和相邻的光学遥感图像功能.
- 使用深度卷积生成对抗网络 (CGAN) 进行初始云移除,结合本地,全球和边缘功能.
- 从相邻的光学图像中采用光谱特征,以精细地去除云层.
主要成果:
- 实现了令人满意的云移除性能,RMSE为0.0391,SAM为0.0729,mSSI为0.9221和CC为0.9537.
- 与经典方法相比,显著改善,指标增强至少为0.0119 (RMSE),0.0438 (SAM),0.0217 (mSSI) 和0.0240 (CC).
- 在边界光滑,消除云阴影,光谱一致性和在各种表面条件下恢复空间细节方面展示了卓越的性能.
结论:
- 拟议的粗细云去除方法有效地提高了光学遥感图像的质量.
- 集成SAR和光学数据,加上深度CGAN网络,为云移除挑战提供了强大的解决方案.
- 这种技术在各种应用中具有显著的潜力,可以提高光学遥感数据的实用性.
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