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Spatiotemporal fusion is important in providing high spatial resolution earth observations with a dense time series, and recently, learning-based fusion methods have been attracting broad interest. These algorithms project image patches onto a feature space with the enforcement of a simple mapping to predict the fine resolution patches from the corresponding coarse ones. However, the sophisticated...
Spatiotemporal reflectance fusion plays an important role in providing earth observation with both high-spatial and high-temporal resolutions, and sparse representation is one of the popular strategies to implement spatiotemporal fusion. However, the existing methods generally suffers from instability of sparse representation for the fine and coarse image pairs. In this paper, we demonstrate that...
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