Cited by 477Image Enhancement TechniquesAdvanced Vision and ImagingComputer Graphics and Visualization Techniques

Vision and rain

Garg, Kshitiz, Nayar, Shree K.·2007·International Journal of Computer Vision

Integrity signals

Registry

Crossref · 10.1007/s11263-006-0028-6

Cites

31 of 31 references verified0 citation errors · 0 not checkable

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Claims the paper makes

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  • In applications that use LIDAR and radar, rain attenuates the strength of the transmitted signals and introduces noise.

    “In applications that use LIDAR and radar, rain attenuates the strength of the transmitted signals and introduces noise [1].”
  • Garg and Nayar [1] broadly classify adverse weather conditions into steady (fog, mist, and haze) or dynamic (rain, snow, and hail).

    “Garg and Nayar [1] broadly classify adverse weather conditions into steady (fog, mist, and haze) or dynamic (rain, snow, and hail).”

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Authors
Garg, K., & Nayar, S. K.
Affiliations
Columbia University (US)
Corresponding author
Garg, Kshitiz
Venue
International Journal of Computer Vision
Published
2007-02-15
Volume
75
Issue
1
Pages
3-27
ISSN
  • 0920-5691 (ISSN-L)
  • 1573-1405
OpenAlex
W1965572510
Cited by
477
References
31
Citations by year
2026: 24 · 2025: 44 · 2024: 23 · 2023: 34 · 2022: 29 · 2021: 59 · 2020: 43 · 2019: 39 · 2018: 25 · 2017: 23 · 2016: 16 · 2015: 23 · 2014: 21 · 2013: 17 · 2012: 20
FWCI
8.75
Type
journal article
Language
en
Open access
closed
Locations
International Journal of Computer Vision (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Enhancement Techniques
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
  • Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Computer Graphics and Visualization Techniques
Keywords
rain streaks, rain removal, rain detection, photometric model, rain rate measurement, video post-processing

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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