• DocumentCode
    1675490
  • Title

    Automatic Detection of Low Light Images in a Video Sequence Shot under Different Light Conditions

  • Author

    Zahi, Gabriel ; Shigang Yue

  • Author_Institution
    Sch. of Comput. Sci., Univ. of Lincoln, Lincoln, UK
  • fYear
    2013
  • Firstpage
    271
  • Lastpage
    276
  • Abstract
    Nocturnal insects have the ability to neurally sum visual signals in space and time to be able to see under very low light conditions. This ability shown by nocturnal insects has inspired many researchers to develop a night vision algorithm, that is capable of significantly improving the quality and reliability of digital images captured under very low light conditions. This algorithm however when applied to day time images rather degrades their quality. It is therefore not suitable to apply the night vision algorithms equally to an image stream with different light conditions. This paper introduces a quick method of automatically determining when to apply the nocturnal vision algorithm by analysing the cumulative intensity histogram of each image in the stream. The effectiveness of this method is demonstrated with relevant experiments in a good and acceptable way.
  • Keywords
    image sequences; reliability; video signal processing; automatic detection; cumulative intensity histogram; day time images; digital image quality; digital image reliability; image stream; low-light condition; low-light images; night vision algorithm; nocturnal insects; nocturnal vision algorithm; video sequence shot; visual signal; Algorithm design and analysis; Educational institutions; Histograms; Insects; Night vision; Noise; Video sequences; Cumulative Histogram; Low Light Detection; Night Vision;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Modelling Symposium (EMS), 2013 European
  • Conference_Location
    Manchester
  • Print_ISBN
    978-1-4799-2577-3
  • Type

    conf

  • DOI
    10.1109/EMS.2013.47
  • Filename
    6779858