Remote sensing images often suffer from cloud cover. Cloud removal is required in many applications of remote sensing images. Multitemporal-based methods are popular and effective to cope with thick clouds. This paper contributes to a summarization and experimental comparation of the existing multitemporal-based methods. Furthermore, we propose a spatiotemporal-fusion with poisson-adjustment method to fuse multi-sensor and multi-temporal images for cloud removal. The experimental results show that the proposed method has potential to address the problem of accuracy reduction of cloud removal in multi-temporal images with significant changes.
@article{arxiv.1707.09959,
title = {Correction of "Cloud Removal By Fusing Multi-Source and Multi-Temporal Images"},
author = {Chengyue Zhang and Zhiwei Li and Qing Cheng and Xinghua Li and Huanfeng Shen},
journal= {arXiv preprint arXiv:1707.09959},
year = {2019}
}
Comments
This is a correction version of the accepted IGARSS 2017 conference paper