A Data Fusion Method For The Delayering Of X-Ray Fluorescence Images Of Painted Works Of Art

In this manuscript, we address the problem of studying layer structure in X-ray Fluorescence (XRF) elemental maps of paintings through the incorporation of reflectance imaging spectral data in the visible or near IR range. We propose a conceptually flexible approach, which involves an initial clustering step for the visible hyperspectral reflectance data (RIS) and the formation of a synthetic surface XRF image. Considering the difference of the full and synthetic surface XRF images, surface and subsurface correlated features are then identified. Results are demonstrated on real and simulated data.