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This paper presents a novel method for the digital reconstruction of spectral reflectance curves of oil paintings using multispectral imaging, integrating linear techniques like pseudo-inverse and principal component analysis with a neural network for improved accuracy. The proposed approach utilizes a feed-forward back-propagation neural network trained on reflectance spectra data, achieving superior performance metrics such as Goodness-of-Fit Coefficient and Root Mean Squared error. Experimental results d

Author

Jader Guerrero

Language

EN