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Antipodally invariant metrics for fast regression-based super-resolution

Author
Pérez, E.; Salvador, J.; Ruiz-Hidalgo, J.; Rosenhahn, B.
Type of activity
Journal article
Journal
IEEE transactions on image processing
Date of publication
2016-03-31
Volume
25
Number
6
First page
2456
Last page
2468
DOI
https://doi.org/10.1109/TIP.2016.2549362 Open in new window
Repository
http://hdl.handle.net/2117/89049 Open in new window
URL
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7445242 Open in new window
Abstract
Dictionary-based super-resolution (SR) algorithms usually select dictionary atoms based on the distance or similarity metrics. Although the optimal selection of the nearest neighbors is of central importance for such methods, the impact of using proper metrics for SR has been overlooked in literature, mainly due to the vast usage of Euclidean distance. In this paper, we present a very fast regression-based algorithm, which builds on the densely populated anchored neighborhoods and sublinear sear...
Citation
Pérez-Pellitero, E., Salvador, J., Ruiz-Hidalgo, J., Rosenhahn, B. Antipodally invariant metrics for fast regression-based super-resolution. "IEEE transactions on image processing", 31 Març 2016, vol. 25, núm. 6, p. 2456-2468.
Keywords
Antipodes, Regression, Spherical Hashing, Spherical hashing, Super-Resolution, Super-resolution
Group of research
GPI - Image and Video Processing Group
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center

Participants

  • Pérez Pellitero, Eduardo  (author)
  • Salvador, Jordi  (author)
  • Ruiz Hidalgo, Javier  (author)
  • Rosenhahn, Bodo  (author)