• DocumentCode
    105606
  • Title

    Efficient Estimation of Reflectance Parameters From Imaging Spectroscopy

  • Author

    Lin Gu ; Robles-Kelly, Antonio A. ; Jun Zhou

  • Author_Institution
    Res. Sch. of Eng., Australian Nat. Univ., Canberra, ACT, Australia
  • Volume
    22
  • Issue
    9
  • fYear
    2013
  • fDate
    Sept. 2013
  • Firstpage
    3648
  • Lastpage
    3663
  • Abstract
    In this paper, we address the problem of efficiently recovering reflectance parameters from a single multispectral or hyperspectral image. To do so, we propose a shapelet based estimator that employs shapelets to recover the shading in the image. The optimization setting presented is based upon a three-step process. The first of these concerns the recovery of the surface reflectance and the specular coefficients through a constrained optimization approach. Second, we update the illuminant power spectrum using a simple least-squares formulation. Third, the shading is computed directly once the updated illuminant power spectrum is obtained. This yields a computationally efficient method that achieves speed-ups of nearly an order of magnitude over its closest alternative without compromising performance. We provide results on illuminant power spectrum computation, shading recovery, skin recognition and replacement of the scene illuminant, and object reflectance in real-world images.
  • Keywords
    image recognition; image restoration; image retrieval; least squares approximations; optimisation; reflectivity; constrained optimization approach; hyperspectral image; illuminant power spectrum; imaging spectroscopy; least-squares formulation; multispectral image; object reflectance; real-world images; reflectance parameters; scene illuminant replacement; shading recovery; shapelet based estimator; skin recognition; specular coefficients; surface reflectance; Multispectral and hyperspectral imaging; inverse methods for imaging spectroscopy; scene analysis; Color; Databases, Factual; Face; Humans; Image Processing, Computer-Assisted; Lighting; Pattern Recognition, Automated; Skin; Spectrum Analysis;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/TIP.2013.2268970
  • Filename
    6532304