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Fast model-based multispectral imaging using nonnegative principal component analysis |
Optics Letters, Vol. 37, Issue 11, pp. 1937-1939 (2012)
http://dx.doi.org/10.1364/OL.37.001937
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Abstract
Estimation of the spectral reflectance of a scene is a critical problem in image processing and computer vision applications. Model-based multispectral imaging, one of the spectral reflectance estimation methods, can effectively reconstruct the full spectrum using a small number of camera shots. However, it is based on iterative optimization and, thus, is computationally too intensive. In this Letter, we modify the iterative optimization problem to a closed-form problem using nonnegative principal component analysis. The proposed method can substantially reduce the computational cost while maintaining the accuracy.
© 2012 Optical Society of America
OCIS Codes
(200.1130) Optics in computing : Algebraic optical processing
(110.4234) Imaging systems : Multispectral and hyperspectral imaging
ToC Category:
Imaging Systems
History
Original Manuscript: December 27, 2011
Revised Manuscript: February 8, 2012
Manuscript Accepted: March 8, 2012
Published: May 24, 2012
Citation
Moon-Hyun Lee, Hanhoon Park, In Ryu, and Jong-Il Park, "Fast model-based multispectral imaging using nonnegative principal component analysis," Opt. Lett. 37, 1937-1939 (2012)
http://www.opticsinfobase.org/ol/abstract.cfm?URI=ol-37-11-1937
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