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Identification of the materials used in the creation of paintings and illuminated manuscripts can provide conservators with knowledge on how to better preserve objects, and supply scholars with information about the provenance of the objects. Significant headway has been made with non-invasive imaging techniques in the past decade. One example is hyperspectral imaging systems that were initially developed for the remote sensing community, and are now more widely applied to assist with art conservation. Although hardware, such as hyperspectral systems, are becoming more widely used, the software to analyze the acquired data is not yet well developed for pigment analysis of artworks. Pigment specific chemical information is derived from hyperspectral data, leveraging spectral signatures to separate out the various artists' materials used in the creation of the artwork. In general, methods of pigment analysis and mapping of paintings in illuminated manuscripts and artworks involve various algorithms and processing steps to create spatial distribution maps of the spectral signatures. When analyzing a particular work, the goals of the analysis are threefold: determine the number of unique pigments (not visual colors) used in the creation of the object; identify the unique pigment reflectance signatures from the data directly or from previously measured library spectra; and map the location and possible distribution of each pigment across the painting. This information is then passed on to conservators and art historians to inform their efforts. Current endmember selection methods involve significant user input, best done by an expert user and are time-consuming. This research examines the accuracy of creating abundance maps (pigment distribution maps) from automatically derived endmembers (using the Maximum Distance algorithm) to create useful information maps to inform conservators. The non-negative lease squares (NNLS) method is used to un-mix the data to create element distribution maps. Algorithms were evaluated with hyperspectral data of Cosmé Tura's Saint Francis Receiving the Stigma, in the collection of the National Gallery of Art, Washington, DC. Results compare well with what is known of the pigment used to create this painting.
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