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There is growing interest in bringing non-invasive laboratory-based analytical imaging tools to field sites to study wall paintings in order to collect molecular information on the macroscale. Analytical imaging tools, such as reflectance imaging spectrometry, have provided a wealth of information about artist materials and working methods, as well as painting conditions. Currently, scientific analyses of wall paintings have been limited to point-measurement techniques such as reflectance spectroscopy (near-ultraviolet, visible, near-infrared, and mid-infrared), X-ray fluorescence, and Raman spectroscopy. Macroscale data collection methods have been limited to multispectral imaging in reflectance and luminescence modes, which lacks sufficient spectral bands to allow for the mapping and identification of artist materials of interest. The development of laboratory-based reflectance and elemental imaging spectrometers and scanning systems has sparked interest in developing truly portable versions, which can be brought to field sites to study wall paintings where there is insufficient space or electrical power for laboratory instruments. This paper presents the design and testing of a simple hyperspectral system consisting of a 2D spatial spot scanning spectrometer, which provides high spectral resolution diffuse reflectance spectra from 350 to 2500 nm with high signal to noise and moderate spatial resolution (few mm). This spectral range at high spectral resolution was found to provide robust chemical specificity sufficient to identify and map many artists' materials, as well as the byproducts of weathering and conservation coatings across the surface of ancient and Byzantine Cypriot wall paintings. Here, we present a detailed description of the hyperspectral system, its performance, and examples of its use to study wall paintings from Roman tombs in Cyprus. The spectral/spatial image processing workflow to make maps of pigments and constituent painting materials is also discussed. This type of configurable hyperspectral system and the imaging processing workflow offer a new tool for the field study of wall paintings and other immovable heritage. [ABSTRACT FROM AUTHOR]

Visible and infrared reflectance imaging spectroscopy is one of the several non-invasive techniques used during Operation Night Watch for the study of Rembrandt's iconic masterpiece The Night Watch (1642). The goals of this project include the identification and mapping of the artists' materials, providing information about the painting technique used as well as documenting the painting's current state and ultimately determining the possible conservation plan. The large size of the painting (3.78 m by 4.53 m) and the diversity of the technical investigations being performed make Operation Night Watch the largest research project ever undertaken at the Rijksmuseum. To construct a complete reflectance image cube at a high spatial resolution (168 µm2) and spectral resolution (2.54 to 6 nm), the painting was imaged with two high-sensitivity line scanning hyperspectral cameras (VNIR 400 to 1000 nm, 2.54 nm, and SWIR 900 to 2500 nm, 6 nm). Given the large size of the painting, a custom computer-controlled 3-D imaging frame was constructed to move each camera, along with lights, across the painting surface. A third axis, normal to the painting, was added along with a distance-sensing system which kept the cameras in focus during the scanning. A total of 200 hyperspectral image swaths were collected, mosaicked and registered to a high-resolution color image to sub-pixel accuracy using a novel registration algorithm. The preliminary analysis of the VNIR and SWIR reflectance images has identified many of the pigments used and their distribution across the painting. The SWIR, in particular, has provided an improved visualization of the preparatory sketches and changes in the painted composition. These data sets, when combined with the results from the other spectral imaging modalities and paint sample analyses, will provide the most complete understanding of the materials and painting techniques used by Rembrandt in The Night Watch. [ABSTRACT FROM AUTHOR]

• While much progress has been made in developing hyperspectral cameras for collecting high quality reflectance image cubes from works of art, little work has been done to create optimized image analysis tools to mine these rich and large data sets. • Automated convex geometry algorithms are good candidates for pigment classification of reflectance imaging spectroscopy (RIS) data from paintings. • The proposed Maximum Distance (MaxD) algorithm performs well with automatic classification of paintings from RIS data cubes. Significant reduction in computation time, as well as a lack of tunable parameters makes this method desirable. • Spectral libraries have great use for visually comparing spectral features to help with pigment identification. Direct matching by algorithm is problematic because of normal variations in hue, scattering and the fact most paint layers are not optical thick enough in the near infrared. Knowledge of pigments and their distribution in paintings can inform conservators and scholars to better understand, and conserve these objects. In recent years, a variety of macro-scale non-contact imaging modalities have been applied to paintings to create classification/material maps. One modality, reflectance imaging spectroscopy (RIS) captures the diffuse reflectance spectral signatures of the artists' materials present in the objects which can be used for classification (by defining regions of the image cube that have the same spectral reflectance signature). In Cultural Heritage Science the ENVI spectral hourglass wizard (ENVI-SHW) has been used to create classification maps from RIS. This method is slow and requires an expert user input during the processing in order to find the reflectance spectra that define the spectral classes (spectral endmembers or exemplars). The pigments are then deduced from spectral features in endmember spectra and from other non-invasive analytical chemical analysis of sites defined by the RIS maps. This paper explores the potential of more automated algorithms, such as maximum distance (MaxD), that are based on the theory of convex hulls for doing these classifications as well as spectral matching algorithms to an optimal spectral library. While all of these algorithms were developed for Remote Sensing community, MaxD and the library matching examine all the spectra in the reflectance image cube, require little user input, and are reproducible and fast. The results from the analysis of reflectance image cubes (400 to 950 nm) of three paintings with MaxD and a spectral library matching algorithm are presented and compared to those obtained with the ENVI-SHW algorithm. The three paintings analyzed are the central panels from illuminated leafs, two from the Laudario of Sant'Agnese (c. 1340) painted by the Master of the Dominican Effigies, namely The Nativity with the Annunciation to the Shepherds and, Christ and the Virgin Enthroned with Forty Saints , and one cutting from a leaf from a Choir book, Saint Francis Receiving the Stigmata , painted by Cosmè Tura (c. 1470s). Specifically, the results include the spectral endmembers recovered from each method as well as the associated classification maps. The findings from this study show that the MaxD algorithm was able to find the majority of the reflectance spectral endmembers with little user input. [ABSTRACT FROM AUTHOR]

The article highlights the using of an elemental (x-ray fluorescence) and molecular (infrared reflectance) imaging spectroscopies in the way two complementary modalities which provided a more complete picture of the development and changes made to the Lamb. It mentions the extraction and characterization of microsamples by light microscopy and microchemical testing.

Two imaging modalities based on molecular and elemental spectroscopy were used to characterize a painting by Cosimo Tura. Visible-to-near-infrared (400-1680 nm) reflectance imaging spectroscopy (RIS) and X-ray fluorescence (XRF) imaging spectroscopy were employed to identify pigments and determine their spatial distribution with higher confidence than from either technique alone. For example, Mary's red robe was modeled through the distribution of an insect-derived red lake (RIS map) and lead white (XRF lead map), rather than a layer of red lake on vermilion. The RIS image cube was also used to isolate the preparatory design by mapping the reflectance spectra associated with it. In conjunction with results from an earlier RIS study (1650-2500 nm) to map and identify the binding media, a more thorough understanding was gained of the materials and techniques used in the painting. [ABSTRACT FROM AUTHOR]