Abstract: We propose an exemplar-based super-resolution algorithm based on sparsity constrained neighbor-embeddings of local image patches.

ABSTRACT. We propose an exemplar-based super-resolution algorithm based on sparsity constrained neighbor-embeddings of local image patches.

This work extracts exemplar patch pairs from as little as the given low-resolution image, and relies on local geometric similarities of low- and ...

We propose an exemplar-based super-resolution algorithm based on sparsity constrained neighbor-embeddings of local image patches. We extract exemplar patch ...

Iris recognition research is heading towards enabling more relaxed acquisition conditions. This has effects on the quality and resolution of acquired images ...

This paper proposes learning based approaches for single image super-resolution using sparse representation and neighbor embedding.

In this paper, we evaluate a super-resolution algorithm used to reconstruct iris images based on iterative neighbor embedding of local image patches which tries ...

Iterated neighbor-embeddings for image super-resolution. (2014). Not Available. Content Type: proceedings-article. Conference: 2014 IEEE International ...

We describe a self-content single-image super-resolution algorithm based on multi-scale neighbor embeddings of small image patches.

This paper proposes a novel method for solving single-image super-resolution problems, given a low-resolution image as input, and recovers its ...