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
Link To Document