Robust super-resolution
By Assaf Zomet, Alex Rav-Acha, Shmuel Peleg. Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, 2001
342 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Media Technology
View Paper: https://www.semanticscholar.org/paper/b029249c325ccc9ca57757ffa88858ef29c02d35
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Michael Elad
- Peyman Milanfar
- Luc Van Gool
- Lei Zhang
- Dacheng Tao
- Radu Timofte
- Matan Protter
- Ming-Hsuan Yang
In Media Technology
- Michael Elad
- Peyman Milanfar
- Matan Protter
- Sina Farsiu
- Hiroyuki Takeda
- A. Gholipour
- Simon Keith Warfield
- Judy A. Estroff
Citations in the corpus
- Super‐resolution methods in MRI: Can they improve the trade‐off between resolution, signal‐to‐noise ratio, and acquisition time? (2012, methodology): “[9] RSR approximates IBP and thus the LS solution.”
- A Frequency Domain Approach to Registration of Aliased Images with Application to Super-resolution (2006, methodology): “They also showed that this approach performs very well in combination with the algorithm by Zomet et al. [ 11 ].”
- Advances and challenges in super‐resolution (2004, methodology): “We call this operation Median Shift-And-Add, which bears some similarity to the median-based algorithm proposed by Zomet et al. (2001).”
- Robust Super-resolution Volume Reconstruction from Slice Acquisitions: Application to Fetal Brain MRI (2010, background): “This problem is not of concern for the L1-norm super-resolution because a closed-form solution exists for ν = 1 [18], [32].”
- Super-Resolution Without Explicit Subpixel Motion Estimation (2009, background): “The existing literature on enhancement and upscaling (sometimes called super-resolution1) is vast and rapidly growing in both the single frame case [1], [2] and the multiframe (video) case [3]–[11], and many new algorithms for this problem have been proposed recently.”
- Fast and robust multiframe super resolution (2004, methodology): “9 (g) was obtained by simply adding the regularization term defined in (25) to the proposed method of [14] which is far better than the approach, yet exhibiting some artifacts.”