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
Link To Document :
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