Open AccessReflectance spectra reconstruction from trichromatic camera based on kernel partial least square method
Author(s) -
Gensheng Xiao,
Xiaoxia Wan,
Lixia Wang,
Shiwei Liu
Publication year - 2019
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.27.034921
Subject(s) - multispectral image , kernel (algebra) , optics , artificial intelligence , trichromacy , square (algebra) , computer science , reflectivity , computer vision , materials science , mathematics , color vision , physics , geometry , combinatorics
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.