Nearest Neighbor Classification for Classical Image Upsampling

Evan Matthews, Nicolas Prate
3/28/2024
cs.CVcs.GR

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Abstract

Given a set of ordered pixel data in the form of an image, our goal is to perform upsampling on the data such that: the resulting resolution is improved by some factor, the final result passes the human test, having added new, believable, and realistic information and detail to the image, the time complexity for upscaling is relatively close to that of lossy upscaling implementations.

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Cite this paper

@article{matthews2024nearest,
  title  = {Nearest Neighbor Classification for Classical Image Upsampling},
  author = {Evan Matthews and Nicolas Prate},
  year   = {2024},
  eprint = {2403.19611},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2403.19611v2}
}

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