• DocumentCode
    2711974
  • Title

    A biquadratic reflectance model for radiometric image analysis

  • Author

    Shi, Boxin ; Tan, Ping ; Matsushita, Yasuyuki ; Ikeuchi, Katsushi

  • Author_Institution
    Univ. of Tokyo, Tokyo, Japan
  • fYear
    2012
  • fDate
    16-21 June 2012
  • Firstpage
    230
  • Lastpage
    237
  • Abstract
    Radiometric image analysis methods heavily rely on reflectance models. Due to the complexity of real materials, methods based on simple models such as the Lambertian model often suffer from inaccuracy. On the other hand, more advanced models such as the Cook-Torrance model severely complicate the analysis problem. We tackle this dilemma by focusing on the low-frequency component of the reflectance. We propose a compact biquadratic reflectance model to represent the reflectance of a broad class of materials precisely in the low-frequency domain. We validate our model by fitting to both existing parametric models and non-parametric measured data, and show that our model outperforms existing parametric diffuse models. We show applications of reflectometry using general diffuse surfaces and photometric stereo for general isotropic materials. Experimental results show the effectiveness of our biquadratic model and its usefulness in radiometric image analysis.
  • Keywords
    image processing; reflectometry; Cook-Torrance model; Lambertian model; biquadratic model; biquadratic reflectance model; general diffuse surfaces; general isotropic materials; low-frequency component; parametric diffuse models; parametric models; photometric stereo; radiometric image analysis; reflectometry; Analytical models; Brain modeling; Computational modeling; Integrated circuit modeling; Materials; Mathematical model; Radiometry;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on
  • Conference_Location
    Providence, RI
  • ISSN
    1063-6919
  • Print_ISBN
    978-1-4673-1226-4
  • Electronic_ISBN
    1063-6919
  • Type

    conf

  • DOI
    10.1109/CVPR.2012.6247680
  • Filename
    6247680