Specularity removal from imaging spectroscopy data via entropy minimisation

Lin Gu*, Antonio Robles-Kelly

*Corresponding author for this work

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

    2 Citations (Scopus)

    Abstract

    In this paper, we present a method to remove specularities from imaging spectroscopy data. We do this by making use of the dichromatic model so as to cast the problem in a linear regression setting. We do this so as to employ the average radiance for each pixel as a means to map the spectra onto a two-dimensional space. This permits the use of an entropy minimisation approach so as to recover the slope of a line described by a linear regressor. We show how this slope can be used to recover the specular coefficient in the dichromatic model and provide experiments on real-world imaging spectroscopy data. We also provide comparison with an alternative and effect a quantitative analysis that shows our method is robust to changes the degree of specularity of the image or the location of the light source in the scene.

    Original languageEnglish
    Title of host publicationProceedings - 2011 International Conference on Digital Image Computing
    Subtitle of host publicationTechniques and Applications, DICTA 2011
    Pages59-65
    Number of pages7
    DOIs
    Publication statusPublished - 2011
    Event2011 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2011 - Noosa, QLD, Australia
    Duration: 6 Dec 20118 Dec 2011

    Publication series

    NameProceedings - 2011 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2011

    Conference

    Conference2011 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2011
    Country/TerritoryAustralia
    CityNoosa, QLD
    Period6/12/118/12/11

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