umu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A variational approach to atmospheric visibility estimation in the weather of fog and haze
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics. Nanjing Univ Posts & Telecommun, Coll Telecommun & Informat Engn, Nanjing, Jiangsu, Peoples R China; Royal Inst Technol, Sch Comp Sci & Commun, Stockholm, Sweden.
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
Show others and affiliations
2018 (English)In: Sustainable cities and society, ISSN 2210-6707, Vol. 39, p. 215-224Article in journal (Refereed) Published
Abstract [en]

Real-time atmospheric visibility estimation in foggy and hazy weather plays a crucial role in ensuring traffic safety. Overcoming the inherent drawbacks with traditional optical estimation methods, like limited sampling volume and high cost, vision-based approaches have received much more attention in recent research on atmospheric visibility estimation. Based on the classical Koschmieder's formula, atmospheric visibility estimation is carried out by extracting an inherent extinction coefficient. In this paper we present a variational framework to handle the nature of time-varying extinction coefficient and develop a novel algorithm of extracting the extinction coefficient through a piecewise functional fitting of observed luminance curves. The developed algorithm is validated and evaluated with a big database of road traffic video from Tongqi expressway (in China). The test results are very encouraging and show that the proposed algorithm could achieve an estimation error rate of 10%. More significantly, it is the first time that the effectiveness of Koschmieder's formula in atmospheric visibility estimation was validated with a big dataset, which contains more than two million luminance curves extracted from real-world traffic video surveillance data.

Place, publisher, year, edition, pages
2018. Vol. 39, p. 215-224
Keywords [en]
Atmospheric visibility estimation, Variational approach, Piecewise stationary time series, Computer vision, Fog and haze
National Category
Other Environmental Engineering
Identifiers
URN: urn:nbn:se:umu:diva-144561DOI: 10.1016/j.scs.2018.02.001ISI: 000433169800020OAI: oai:DiVA.org:umu-144561DiVA, id: diva2:1180671
Available from: 2018-02-06 Created: 2018-02-06 Last updated: 2018-09-05Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Authority records BETA

Cheng, XiaogangYang, BinOlofsson, Thomas

Search in DiVA

By author/editor
Cheng, XiaogangYang, BinOlofsson, Thomas
By organisation
Department of Applied Physics and Electronics
In the same journal
Sustainable cities and society
Other Environmental Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 101 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf