  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.
