Super-resolution method using sparse regularization for point-spread function recovery

16 Oct 2014 • Fred Maurice Ngolè Mboula • Jean-Luc Starck • Samuel Ronayette • Koryo Okumura • Jérôme Amiaux

In large-scale spatial surveys, such as the forthcoming ESA Euclid mission, images may be undersampled due to the optical sensors sizes. Therefore, one may consider using a super-resolution (SR) method to recover aliased frequencies, prior to further analysis... (read more)

PDF Abstract

Code
Add Remove Mark official

No code implementations yet. Submit your code now

Tasks
Add Remove

Datasets

  Add Datasets introduced or used in this paper

Results from the Paper
Add Remove

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper
Add Remove

METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet
Contact us on: hello@paperswithcode.com. Papers With Code is a free resource with all data licensed under CC-BY-SA.
Terms Privacy Cookies policy