Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/4603
Title: Optimal selection of representative colors for spectral reflectance reconstruction in a multispectral imaging system
Authors: Shen, Hui-liang
Zhang, Hong-Gang
Xin, John Haozhong
Shao, Sijie
Subjects: Computer networks
Digital image storage
Electromagnetic waves
Image processing
Image reconstruction
Imaging systems
Optoelectronic devices
Reflection
Restoration
Issue Date: 1-May-2008
Publisher: Optical Society of America
Source: Applied optics, 1 May 2008, v. 47, no. 13, p. 2494-2502.
Abstract: In a multispectral color imaging system, the spectral reflectance of the object being imaged always needs to be accurately reconstructed by employing the training samples on specific color charts. Considering that the workload is heavy when all those color samples are used in practical applications, it is important to select only a limited number of the most representative samples. This is possible as the color charts are usually designed to cover the range of commonly imaged colors, and the color samples are redundant for spectral image reconstruction. We propose an eigenvector-based method and a virtual-imaging-based method for representative color selection by minimizing the total reflectance root-mean-squares errors. The effectiveness of the proposed methods is confirmed by experimental results when compared with existing techniques.
Rights: © 2008 Optical Society of America. This paper was published in Applied Optics and is made available as an electronic reprint with the permission of OSA. The paper can be found at the following URL on the OSA website: http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-47-13-2494. Systematic or multiple reproduction or distribution to multiple locations via electronic or other means is prohibited and is subject to penalties under law.
Type: Journal/Magazine Article
URI: http://hdl.handle.net/10397/4603
DOI: 10.1364/AO.47.002494
ISSN: 0003-6935
Appears in Collections:ITC Journal/Magazine Articles

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