Corpus ID: 58004741

Neumann Networks for Inverse Problems in Imaging

@article{Gilton2019NeumannNF,
  title={Neumann Networks for Inverse Problems in Imaging},
  author={Davis Gilton and Greg Ongie and R. Willett},
  journal={ArXiv},
  year={2019},
  volume={abs/1901.03707}
}
  • Davis Gilton, Greg Ongie, R. Willett
  • Published 2019
  • Computer Science, Mathematics
  • ArXiv
  • Many challenging image processing tasks can be described by an ill-posed linear inverse problem: deblurring, deconvolution, inpainting, compressed sensing, and superresolution all lie in this framework. Traditional inverse problem solvers minimize a cost function consisting of a data-fit term, which measures how well an image matches the observations, and a regularizer, which reflects prior knowledge and promotes images with desirable properties like smoothness. Recent advances in machine… CONTINUE READING
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