Reflectance spectra reconstruction from trichromatic camera based on kernel partial least square method

被引:19
作者
Xiao, Gensheng [1 ,2 ]
Wan, Xiaoxia [1 ,3 ]
Wang, Lixia [1 ]
Liu, Shiwei [2 ]
机构
[1] Wuhan Univ, Sch Printing & Packaging, Wuhan 430079, Peoples R China
[2] Henan Univ Anim Husb & Econ, Sch Packaging & Printing Engn, Zhengzhou 450011, Peoples R China
[3] Hubei Prov Engn Tech Ctr Digitizat & Virtual Repr, Wuhan 430079, Peoples R China
基金
中国国家自然科学基金;
关键词
LINEAR-MODELS; RECOGNITION; SELECTION; RECOVERY; SYSTEM;
D O I
10.1364/OE.27.034921
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
A novel spectral reflectance reconstruction method based on kernel partial least square (KPLS) regression is proposed. The proposed method integrates the partial least square algorithm and kernel function to estimate the reflectance spectra from 9-channel multispectral imaging system using commercial trichromatic camera. The performance of the proposed method is demonstrated in comparison with the existing methods using simulated and real camera responses from Munsell Matte color and IT8.7/3 dataset. The experimental results show that the proposed method is superior or at least equivalent to its counterparts and satisfactory enough for color management purpose. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
引用
收藏
页码:34921 / 34936
页数:16
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