Abstract

The presence of cloud shadows on remotely sensed images significantly complicates the analysis of the monitored area. The paper considers the problem of cloud shadows compensation on multispectral remotely sensed data. A new algorithm for cloud shadows detection and compensation based on a robust estimate of a local shadowing coefficient is proposed. Experimental results on shadow compensation quality for RGBN channels and Normalized Difference Vegetation Index (NDVI) index using the dataset of ten Sentinel-2 satellite multispectral images are presented. The results show that the compensation effect by the proposed algorithm on RGBN and NDVI data is 2 times better than that of the Gray-World-based algorithm.

中文翻译：

---

农区多光谱卫星影像云影检测与补偿算法

摘要

遥感图像上云阴影的存在使监测区域的分析变得非常复杂。研究了多光谱遥感数据的云影补偿问题。提出了一种基于局部阴影系数鲁棒估计的云阴影检测与补偿新算法。给出了使用 10 个 Sentinel-2 卫星多光谱图像数据集对 RGBN 通道和归一化差异植被指数 (NDVI) 指数进行阴影补偿质量的实验结果。结果表明，该算法对RGBN和NDVI数据的补偿效果是基于Gray-World算法的2倍。