Improvement of spectral imaging by pigment mapping

Yonghui Zhao
Roy Berns
Yoshio Okumura

"Improvement of spectral imaging by pigment mapping," Proceedings of the Thirteenth Color Imaging Conference. The Society for Imaging Science and Technology. Held in Scottsdale, Arizona: November 2005. This article may be accesssed on the publisher's website (additional fees may apply) at: This research is part of the Art Spectral Imaging project, supported by the Andrew W. Mellon Foundation, the National Gallery of Art, Washington, DC and the Museum of Modern Art, New York. ISBN:0-89208-259-3Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works in February 2014.


Spectral imaging has been widely developed over the last ten years for archiving cultural heritage. It can retrieve spectral reflectance of each scene pixel and provide the possibility to render images for any viewing condition. A new spectral reconstruction method, the matrix R method, can achieve high spectral and colorimetric accuracies simultaneously for a specific viewing condition. Although the matrix R method is very effective, the reconstructed reflectance spectrum is not smooth when compared with in situ spectrophotometry. The goal of this research was to smooth the spectrum and make it more accurate. One possible solution is to identify pigments and find their compositions for each pixel. After that, the reflectance spectrum can be modified based on two-constant Kubelka-Munk theory using the absorption and scattering coefficients of these pigments, weighted by their concentrations. The concentrations were optimized to best fit the spectral reflectance predicted by the matrix R method. As a preliminary experiment, it was assumed that a custom target was painted using several known pigments. The simulation results show that incorporating pigment mapping into the matrix R method can recover the smoothness of the reflectance spectrum, and further improve spectral accuracy of spectral imaging.