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