Computational Conservation and Art History: Examples from Emerging Fields

The advent of advanced high-resolution imaging techniques, including digital photography, hyperspectral imaging, and macro-XRF, has brought a transition from not having enough data about cultural heritage objects to having too much to easily process. Combining techniques from microstructural analysis, scale space theory, machine learning, and interactive data visualization, it is possible to fuse this data and to draw a wide range of new insights about the condition and history of art objects.