Accurate Blur Models vs. Image Priors in Single Image Super-resolution

@article{Efrat2013AccurateBM,
  title={Accurate Blur Models vs. Image Priors in Single Image Super-resolution},
  author={Netalee Efrat and Daniel Glasner and Alexander Apartsin and Boaz Nadler and Anat Levin},
  journal={2013 IEEE International Conference on Computer Vision},
  year={2013},
  pages={2832-2839}
}
Over the past decade, single image Super-Resolution (SR) research has focused on developing sophisticated image priors, leading to significant advances. Estimating and incorporating the blur model, that relates the high-res and low-res images, has received much less attention, however. In particular, the reconstruction constraint, namely that the blurred and down sampled high-res output should approximately equal the low-res input image, has been either ignored or applied with default fixed… CONTINUE READING
Highly Cited
This paper has 157 citations. REVIEW CITATIONS
42 Citations
27 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 42 extracted citations

158 Citations

020406020142015201620172018
Citations per Year
Semantic Scholar estimates that this publication has 158 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 27 references

Accurate blur models vs. image priors in single image superresolution - supplementary results

  • N. Efrat, D. Glasner, A. Apartsin, B. Nadler, A. Levin
  • 2013
Highly Influential
5 Excerpts

Similar Papers

Loading similar papers…