Temporal Domain Group Sparse Representation Based Cloud Removal for Remote Sensing Images

The reconstruction of the missing information of optical remote sensing images contaminated by unwanted cloud has attracted a great deal of attention. However, in practice, cloud removal is a challenging problem. In this paper, we propose to reconstruct the missing information by temporal domain group sparse representation. With the help of temporal normalization, the temporal complementation of multitemporal remote sensing images is strengthened. The group sparse representation, which seeks similar patches from the temporal domain, is then applied to recover the missing information. The experiments demonstrated that the proposed method is both quantitatively and qualitatively effective.

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