Spectral reflectance reconstruction is the key technology of multi-spectral color reproduction, and it solves the exact color information restoring of original scene to provide color information support for high-fidelity reproduction. The current mainstream principal component analysis method is suitable for information reconstruction of simple objects and smooth objects, and the independent component analysis method is adaptive for color main component extraction of complex objects or scenes. Integrating the advantages of these two methods and imported blind source signal estimation theory, this study highlights the adaptive component analysis method for spectral reflectance reconstruction. Firstly it clarified the reconstruction principle and method of adaptive component analysis methods, and then it carried on the spectral reflectance reconstruction test by selecting the typical color lumps of Finland University “AOTF Munsell Color Matt” spectrum dataset. The results showed the reconstruction precision was higher and the spectral matching skewness index was very small (less than 0.020 basic), besides the reconstruction efficiency was higher and the method adaptability was stronger. Moreover, this study provided a new theoretical interpretation for Color Constancy Theory of human vision.
Haiwen Wang, Jie Li, Xiaoxia Wan, Ling Lu, "Research on Adaptive Component Analysis Method of Spectral Reflectance Reconstruction" in Journal of Imaging Science and Technology, 2022, pp 020403-1 - 020403-5, https://doi.org/10.2352/J.ImagingSci.Technol.2022.66.2.020403