Image Segmentation and Pigment Mapping of Cultural Heritage Based on Spectral Imaging

The goal of the work reported in this dissertation is to develop methods for image segmentation and pigment mapping of paintings based on spectral imaging. To reach this goal it is necessary to achieve sufficient spectral and colorimetric accuracies of both the spectral imaging system and pigment mapping. The output is a series of spatial distributions of pigments (or pigment maps) composing a painting. With these pigment maps, the change of the color appearance of the painting can be simulated when the optical properties of one or more pigments are altered. These pigment maps will also be beneficial for enriching the historical knowledge of the painting and aiding conservators in determining the best course for retouching damaged areas of the painting when metamerism is a factor. First, a new spectral reconstruction algorithm was developed based on Wyszecki’s hypothesis and the matrix R theory developed by Cohen and Kappauf. The method achieved both high spectral and colorimetric accuracies for a certain combination of illuminant and observer. The method was successfully tested with a practical spectral imaging system that included a traditional color-filter-array camera coupled with two