Thick Cloud Removal for Sentinel-2 Time-Series Images via Combining Deep Prior and Low-Rank Tensor Completion

In this study, we combine both the deep prior with low-rank tensor completion (DP-LRTC) for thick cloud removal in Sentinel-2 time-series images. On the one hand, DP-LRTC utilizes the low-rank property of multitemporal images via 3-order tensor completion. On the other hand, DP-LRTC employs the 3D spatiotemporal feature expression ability by deep learning. Through integrating both model-driven with data-driven strategy, the proposed method can effectively removal thick cloud in Sentinel-2 time-series images.