Improved single image dehazing using geometry

Peter Carr*, Richard Hartley

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    73 Citations (Scopus)


    Images captured in foggy weather conditions exhibit losses in quality which are dependent on distance. If the depth and atmospheric conditions are known, one can enhance the images (to some degree) by compensating for the effects of the fog. Recently, several investigations have presented methods for recovering depth maps using only the information contained in a single foggy image. Each technique estimates the depth of each pixel independently, and assumes neighbouring pixels will have similar depths. In this work, we employ the fact that images containing fog are captured from outdoor cameras. As a result, the scene geometry is usually dominated by a ground plane. More importantly, objects which appear towards the top of the image are usually further away. We show how this preference (implemented as a soft constraint) is compatible with the alpha-expansion optimization technique and illustrate how it can be used to improve the robustness of any single image dehazing technique.

    Original languageEnglish
    Title of host publicationDICTA 2009 - Digital Image Computing
    Subtitle of host publicationTechniques and Applications
    Number of pages8
    Publication statusPublished - 2009
    EventDigital Image Computing: Techniques and Applications, DICTA 2009 - Melbourne, VIC, Australia
    Duration: 1 Dec 20093 Dec 2009

    Publication series

    NameDICTA 2009 - Digital Image Computing: Techniques and Applications


    ConferenceDigital Image Computing: Techniques and Applications, DICTA 2009
    CityMelbourne, VIC


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