Cluster-based image super-resolution via jointly low-rank and sparse representation
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文摘

A novel algorithm for single image super-resolution uses the cluster as the basic unit.

The algorithm can enforce global constraint and capture local structure.

We research the appropriate numbers of exemplars for low and high frequency patches.

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