Generalizing the Nonlocal-Means to Super-Resolution Reconstruction
Technion – Israel Institute of Technology · University of California, Santa Cruz
Abstract
Super-resolution reconstruction proposes a fusion of several low-quality images into one higher quality result with better optical resolution. Classic super-resolution techniques strongly rely on the availability of accurate motion estimation for this fusion task. When the motion is estimated inaccurately, as often happens for nonglobal motion fields, annoying artifacts appear in the super-resolved outcome. Encouraged by recent developments on the video denoising problem, where state-of-the-art algorithms are formed with no explicit motion estimation, we seek a super-resolution algorithm of similar nature that will allow processing sequences with general motion patterns. In this paper, we base our solution on…
Citation impact
- FWCI
- 36.91
- Percentile
- 100%
- References
- 54
Authors
4Topics & keywords
- Artificial intelligence
- Motion estimation
- Computer vision
- Computer science
- Noise reduction
- Motion (physics)
- Image resolution
- Superresolution