Image super-resolution
Citations
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Cites background from "Image super-resolution"
...Image super-resolution, reconstructing a higher-resolution image or image sequence from the observed low-resolution image [190], is an exciting application of deep learning methods....
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Cites background from "Image super-resolution"
...Instead of devoting to physical imaging technology, many researchers aim to recover highresolution images from low-resolution ones using an image processing technology called super-resolution [1]....
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References
1,457 citations
"Image super-resolution" refers background or methods in this paper
...Therefore, most of the recent representative arti cles about SR have focused on regularized frameworks [1,47,49,53,54,68,72,73]....
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...[54] adapted kernel regression to multi-frame SR, and this method is able to handle video sequences with general motion models....
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...The popular spatial domain methods include non-uniform interpolation [35], iterative back-projection (IBP) [56], projection onto convex sets (POCS) [57,63,70], the regularized methods [34,40,43,47,53,54,58,62], and a number of hybrid algorithms [71]....
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1,438 citations
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1,397 citations
"Image super-resolution" refers methods in this paper
...Compared with the TV model, the nonlocal-based model can make use of more information, and can thus prevent the staircase effect in flat regions, and can help restore the details [97,113]....
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1,276 citations
"Image super-resolution" refers methods in this paper
...Other researchers have developed regressionbased methods and some improved algorithms, such as the SR method with sparse NE [156], image SR using nonlocal autoregressive modeling [159], and anchored neighborhood regression [171] for fast example-based SR....
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