This PDF file contains the front matter associated with SPIE Proceedings Volume 11784 including the Title Page, Copyright information, and Table of Contents.

Recent advances on micro Spatially Offset Raman Spectroscopy (micro-SORS), an optical spectroscopy method able to non-invasively investigate at the microscale the molecular composition of the subsurface of turbid materials, will be presented. The recent research topics include the application of micro-SORS to non-invasively reconstruct the diffusion profiles of conservation treatments applied in calcium-based matrices, the first in-situ surveys of prestigious panel paintings with a portable micro-SORS prototype derived modifying a commercial portable Raman spectrometer, and proof-of-concept experiments performed coupling micro-SORS with Time-Gated Raman Spectral Multiplexing method for the non-invasive suppression of the fluorescence originated by the subsurface.

Recently a new trend towards a more systematic use of Reflectance Hyperspectral imaging (HSI) has emerged in major museums. Extensive acquisition of HSI data opens up new research topics in terms of comparative analysis, creation and population of spectral databases, linking and crossing information. However, a full exploitation of these big-size data-sets unavoidably raises new issues about data-handling and processing methods. Along with statistical and multivariate analysis, new solutions can be borrowed from the Artificial Intelligence (AI) area, using Machine Learning (ML) and Deep Learning (DL) methods. In this work different algorithms based on multivariate analysis and Artificial Intelligence methods are comparitevely applied to process HSI data acquired on three Picasso’ paintings from the Museu Picasso collection in Barcellona. By using a “data-mining approach” the HSI-data are examined to unveil new correlations and extract embedded information.

This study sets out to analyse the artistic materials used in the maritime Southeast Asian manuscript collection at the British Library. To gain a full understanding of how artistic practises may have developed over time and changed between regions, it is necessary to perform large scale scientific analysis. Visible/NIR spectral imaging is an efficient method of collecting spectral reflectance data which can be used to distinguish different materials. Recent advancements in automatic data collection have meant that the volume of data collected has greatly increased, making traditional approaches to data analysis impossible to perform in a timely manner. Machine learning provides a viable solution to this as it can be used to automatically cluster millions of spectra into smaller, more manageable numbers of distinct spectral groups. Self-organising Maps are used as the building blocks of an algorithm which can perform clustering of large collections of spectral imaging data. Spectral reflectance alone is often not enough to perform pigment identification, consequently other complementary techniques are required. Advances in spectral imaging mean that each of these complementary techniques has a corresponding imaging modality. The machine learning approach developed in this project can be adapted to allow for the clustering of multimodal spectral imaging data including VIS/NIR hyperspectral imaging, macro-X-Ray fluorescence mapping, macro-Raman mapping, and Fourier transform infrared mapping. For multimodal clustering, each modality can be clustered individually and then brought together to produce a single cluster map which is a more refined representation of the material distribution than that produced from any individual spectral imaging modality.   A visualisation tool has also been developed for the easy interpretation and interrogation of spectral imaging data cubes and cluster maps for entire collections. Both the visualisation tool and clustering method will be made accessible to the cultural heritage community through an online DIGILAB platform.

While heritage science in museums usually focuses on the analysis of a single or a few iconic objects, material analysis of archival collections often deals with documents at mass-scale. In this setting, automation of data acquisition and data processing becomes particularly relevant. The analysis of a collection of Tudor maps of Ireland from the National Archives, London, serves as a case study to both test the applicability, and to optimise the methodology, of AI-based spectral clustering on data extracted from a commercial multiband imaging system, used typically for single-band and colour RGB imaging of archival documents, manuscripts and artworks on paper. The clusters revealed important information about the maps’ materiality, such as highlighting the different composition of painted areas within and across maps that appeared very similar in colour with the naked eye or differentiating original ink from later annotations, for instance. The clusters guided the selection of areas for further spectroscopic point analysis, both to check the performance of the algorithm and to interpret the material composition of the different clusters, with the ultimate goal of shading light on Tudor mapmaking practices. Strengths and aspects to be optimised in the methodology are finally discussed.

The sketches of painted cultural objects can be the most indicative of the style of paintings. Extraction of the sketches is an integral process used by conservators and art historians for documentation and for artists to learn historical painting styles through copying and painting. However, at present, sketch extraction is mainly manually drawn, which is not only time-consuming, but also subjective and dependent on experience. Therefore, both accuracy and efficiency need to be improved. In recent years, with the development of machine learning, a series of extraction methods based on edge detection have emerged. However, most of the existing methods can only perform successful extraction if the sketches are well preserved , but for the data with faded sketches or severe conservation issues, the extraction methods need to be improved. It is beneficial to extract the bands that accentuate the sketches while suppressing the effects of the degraded areas and the overlapping paints. We propose a sketch extraction method based on hyperspectral image and deep learning. Firstly, the hyperspectral image data is collected and the bands sensitive to the sketches are extracted by a prior knowledge of the sketches (e.g. near infrared bands will be chosen if the sketches are made of carbon ink), and a dataset including a large number of existing natural images is used to pre-train the bi-directional cascade network (BDCN). The network parameters in the model are then fine-tuned by using the images of painted cultural objects drawn by experts, so as to solve the problem of insufficient sketch dataset of painted cultural objects and enhance the generalization ability of the model. Finally, the U-net network is used to further suppress the noise, i.e. unwanted information, and make the sketch clearer. The experimental results show that the proposed method can not only effectively extract sketch from ideal data, but also extract clear sketches from data with faded sketches and even with noise interference. It is superior to the other six advanced based on edge detection methods in visual and objective comparison, and has a good application prospect. The proposed deep learning method is also compared with an unsupervised clustering method using Self-Organising Map (SOM) which is a ‘shallow learning’ method where pixels of similar spectra are grouped into clusters without the need for data labeling by experts.

Recent advances in technology have brought major breakthroughs in deep learning techniques. In this work, we elaborate on such techniques for output data of image processing performed on craquelure patterns in historical paintings. Historical painted objects, especially panel paintings, with their long environmental history, exhibit complex crack patterns called craquelures. These are cracks in paintings that can be referred to as ‘edge fractures’ as they are initiated from the free surface. The analysis has been conducted on the set of selected craquelure patterns on which recent deep learning methods i.e. Neural Networks algorithm is implemented and the results of such self-learning process are discussed.

In the preservation and restoration of murals, labeling and recording the location and size of the paint loss disease can bring convenience to the subsequent restoration work. At present, the most common method of disease labeling is to draw the disease area manually on an orthophoto map by human-computer interaction. However, this method not only requires much time, but also leads to different labeling results due to different experts' experience. In recent years, with the development of artificial intelligence, machine learning and other technologies, it is possible to realize intelligent labeling through image processing and other methods. Therefore, this paper focuses on the mural paint loss disease and tries to explore the intelligent disease labeling method, hoping to efficiently and accurately mark the paint loss disease. In this paper, firstly, the disease labeling is transformed into an image segmentation problem, and proposes a mural paint loss disease labeling based on U-Net. However, it was experimentally found that much detailed information is often lost when the U-Net is used directly. Therefore, this paper further proposes multi-scale detail injection U-Net, including the constructed multi-scale module and the method of injecting shallow features into in-depth features, which could effectively extract more abundant edge information and improve the labeling accuracy. Furthermore, we demonstrate that the method proposed in this paper could actually achieve the intelligent labeling of the paint loss disease through the murals of the Liao Dynasty Feng Guo Temple in Yi County, Jinzhou City, China.

The investigation of artworks of cultural heritage is generally aimed at the characterization of the constituent materials and the evaluation of their state of conservation. Research may shed light on the pigments and their potential deterioration mechanisms, and on the conservation treatments. Laboratory analysis on micro-samples taken from the artwork is still an invaluable practice for a deep understanding of the paint layer composition. In this context, a powerful technique is spectral microscopy, which acquires the spectrum for each point in the image of a sample. To acquire a continuous spectrum, one very efficient method is based on Fourier-transform (FT) spectroscopy as it allows massive parallelization on all the image pixels. Here we introduce a hyperspectral microscope based on an innovative FT spectrometer; the device is compact, robust, with high throughput and broad spectral coverage. In our microscope, light is collected by an infinity-corrected objective, propagates in the innovative spectrometer and is imaged on a silicon monochrome CMOS camera by a tube lens. The typical spectral resolution of the microscope, which can be flexibly adjusted for each measurement, is 3 THz (4 nm at 600 nm). We show very compact implementations of the hyperspectral microscope and their use for wide-field imaging of reflection, fluorescence and, interestingly, fluorescence-free Raman spectra. Thanks to the high throughput, the acquisition time of our microscope is significantly shorter than traditional raster-scanning approaches.

Natural dyes pose problems concerning their non-invasive identification in artefacts when most of the techniques usually employed for “in-situ” analysis of coloring materials are used. Nowadays, surface-enhanced Raman spectroscopy (SERS) is currently employed to recognise dyes extracted from textiles, as well as applied to extractionless analysis directly on fibers. Nevertheless, there is still a demand for a method based on SERS suitable for the “in-situ” identification of the dyes on intact fabrics in museums. The enhancement of the Raman scattering in SERS is due to two different mechanism, an electromagnetic and a chemical one. The former contributes to the SERS intensification in an order of magnitude of 1010, while the latter of 102. Therefore, in principle, the SERS enhancement can be observed also in absence of a chemisorption and thus, a dry-state analysis leading to a completely non-invasive approach should be possible. In this context, we are studying the possibility of using thin films obtained by deposition of silver colloids on an optically transparent support, i.e. a glass slide, to prepare in an easy way SERS probes suitable for “in situ” analysis by means of portable Raman instrumentation. Silver nanospheres obtained by different methods [2,3] or, alternatively, silver nanostars [4] were deposited on glass slides functionalised with (3-aminopropyl)trimethoxysilane, to promote the adherence and prevent the so-called “coffee ring” effect. The films were tested for the identification of anthraquinonic dyes by a portable Raman micro-probe in mock-up samples of dyed textile fibres. The possibility of embedding the nanoparticles into a polymeric matrix will be also considered to ensure higher stability and a lower impact on the examined object. Finally, we exploited for the first time, at least to the best of our knowledge, commercial electrochemically-deposited substrates (SERSitive) to observe dry-state SERS, obtaining positive results that encourage in perspective to experiment the electrochemical path to produce suitable substrates for our purposes.

We demonstrate the use of a wide-field, compact and ultra-stable hyperspectral camera, based on the Fourier-transform approach [1], to investigate the photoluminescence emission occurring from different radiative recombination paths in artist materials and paintings. The camera, based on the translating wedge-based identical pulse encoding system (TWINS), is characterized by high spectral resolution, high flexibility and compactness. Thanks to these latter feature we show how the device can be easily adapted for both microscopy measurements and remote time-gated imaging of paintings and we show its use for the identification and mapping of fluorescent species in artworks by also exploiting the potentiality provided by chemometrics methods.

Terahertz (THz) radiation in the frequency range 0.1 - 10 THz began to be used for the analysis of artwork in 2006. Terahertz images of paintings require computer processing in order to optimize the process of detecting defects and their visualization. In this work, an algorithm for solving this problem is proposed in relation to the terahertz analysis of paintings. A program is written in Python that searches, group and highlight defects in an image. To work with images, the methods of the OpenCV library is used, designed to solve computer vision problems. They are used to binarize images and search the defect contours on them, as well as to isolate defects when visualizing the results. The grouping of defects is carried out by the method of agglomerative hierarchical clustering. Scientific analysis of the materials used in art items allows to determine the period in which they were created, how they were preserved over the centuries and how they were restored. As part of the study, in this work, a 3D-model of the crystal structure of the red pigment was created. For this, the terahertz spectrum of the pigment was modeled by the density functional method. To experimentally study the optical characteristics of the pigment, measurements are carried out on a TeraView-4000 instrument in transmission mode. The pigment is measured in powder and tableted form.

This contribution discusses the improvement approaches of Terahertz Time-Domain Spectroscopy (THz-TDS) to cultural heritage objects. The technique is gathering attention in the conservation field for its ability to retrieve information on material composition and surface topography in the far-infrared region (3-300 cm⁻¹ ), but it can pose major challenges when applied on works of art. THz-TDS generates hyperspectral images that are corrupted by frequency-dependent blur and noise and are distorted by surface warping. These degradation effects can make the analysis of heterogeneous materials rather complicated because they substantially limit the frequency range where THz images have good spatial resolution and hinder the identification of materials. This work tackles these inherent limitations of the THz-TDS imaging and shows how to improve the analysis by computationally restoring the hyperspectral data. The experiments were undertaken using a bench-top THz-TDS instrument equipped with an advanced laser design and a precise mechanical delay stage that can achieve a peak dynamic range of 100 dB and a bandwidth of more than 6 THz. The exploitable region of frequencies is limited, however, between 0.2 and 3.5 THz because of the size of the THz beam waist and noise present at high frequencies. Such limitations were addressed by adopting a twofold computational strategy that involves (i) the removal of the surface warping and (ii) the application a fast deblurring-denoising algorithm for image restoration tailored to THz images. Experiments undertaken on an archaeological coin demonstrate how the approach effectively reduces degradation effects and how unwanted surface warping (whether it is a simple tilted plane or a more complex distortion) can be removed. The computational restoration of the images significantly improves their resolution, enabling the analysis above 4 THz. The application of such computational strategies makes possible the characterisation of artistic and archaeological materials up to 250 cm⁻¹ . These results concretely open new possibilities in the use of THz spectroscopy imaging on objects with complex geometries and push the boundaries of THz data and image processing.

Digital Holographic Speckle Pattern Interferometry has already been developed for preventive conservation and can monitor directly the changes at the surface of artworks. The system is based on speckle interferometry with phase-shift and gives the deformation of the analysed object. The existing data process consists of removing the noise of the interferogram, unwrapping this image and deriving and displaying 2D or 3D map deformation. To improve the time duration and accuracy of data imaging treatment, we developed an easier and faster processing method. We created a denoising methodology of interference pattern generated during data acquisition based on stationary wavelet transform.

In the last 100 years concrete and steel have been the most common building materials, that is the reason why they constitute the core of the structures on which the architecture of the 20th’s century is based. Both materials present high resistance and durability but the recent collapse of Minardi Bridge in Italy shows that it is absolutely necessary to carry out real-time monitoring of the conservation status of concrete. In this sense, the building of the Agencia Impositiva Federal (A.F.I.P.) which is located in the city of Paran´a, built in the 70s, represents a clear example of brutalist architecture in Argentina. After 40 years of its construction and during remodelling tasks, serious problems in the concrete structures were discovered that forced the evacuation of the building. In order to develop an in situ monitoring system that allows the premature detection of structural problems in 20th’s century heritage buildings, it was implemented an innovative scheme based on digital holographic interferometry (DHI) which includes a semiconductor laser, optical fibre and and ah hoc plastic support made by 3D printing. This system was tested on concrete specimens sujected to dynamic loads in the range of 1 × 10³ kg to 28 × 10³ kg using an Amsler hydraulic press. Results, though preliminary, showed that it is possible to measure in situ the radial deformation of normalised cylindrical specimens under pressure loads and indicated that this low cost, novel DHI set up, could be applied in situ, as a preventive conservation method, to detect cracks and other defects in monumental concrete works.

Efficient monitoring of large-scale cultural heritage monuments is of great interest in understanding alteration mechanisms that lead to substantial decision making for safeguarding them. This work presents a methodological approach for monitoring areas of the wall of King Jan III’ palace Wilanów (Poland), where due to weathering the documentation of the surface changes became indispensable. Data from 3D scanning and registered data, representing different time intervals, were analysed to determine surface geometry changes. The goal was to develop a methodology which could detect each surface point based on grouping it with similar behaviour of local geometry changes. Further analyses, to determine the direction of change and the local geometry, were performed with the goal to extract information on the behaviour of changes and quantify them. By assigning a gradual scale, for the calculated displacement information regarding alterations can be visualized and measured. The methodology was based on calculating initially the general direction of change and then analysing the local geometry changes based on considering neighbouring points obtained from the spherical search kernel of each surface point. The neighbouring points were then compared to weathered dataset point cloud, by calculating the Euclidean distance and data segmentation, based on histograms of local distance analysis, was produced. Each histogram was fitted to the kernel distribution curve and bandwidth parameters, with similar points, were identified and segmented for changes corresponding to different time intervals. Initial evaluation on the case study shows the ability of the proposed methodology to detect even minor surface displacements.

In this paper, a method for artworks monitoring is proposed, able to perform simultaneously speckle interferometry and speckle photography, thus the system can map both out-of-plane and in-plane displacements. The aim is to keep it as simple as possible to increase its possibilities to be routinely used in restoration laboratories. Though simple, the proposed method is tailored to some specific needs of artwork diagnostics.

Structural delamination in mural paintings is a complex phenomenon and is considered among the most frequent types of damage. In conservation practice, the most common technique to identify structural detachments in wall paintings is the percussion method, otherwise known as the ‘tap and listen’ approach. Full-field optical techniques based on interferometry, such as shearography, can potentially provide a more scientifically substantiated evaluation of the condition of heterogeneous structures of wall paintings. The empirical nature of the percussion method was observed during the condition assessment of two medieval wall paintings in Maria Church, Nisse, Netherlands. Consequently, the need to obtain more knowledge regarding the structural condition of these wall paintings was established. Furthermore, to allow the formulation of specific treatment needs for structural delamination in wall paintings, accurate defect mapping is needed. The application of shearography coupled with thermography was believed to provide an holistic representation of the structural condition of the wall painting depicting St. Christopher in Maria Church. A comparison of the practical execution and the interpretation of data between shearography and the percussion method was conducted to deliver a description of both techniques. Initial comparison of the two methods confirmed what was already hypothesised: I) the percussion method can provide an approximate indication of delaminated areas. Results, which are considered both non-qualitative and non-quantitative, are dependent on the experience of the conservator; II) shearography can produce qualitative and quantitative results regarding the presence of delamination in complex structures of wall paintings. Analysis of the shearography data together with the percussion method may result in a reliable way to map the defects for future conservation activities. The next steps include optimisation of the thermal excitation for shearography to maximise the defect detection and adapt the shearography output for onsite interpretation by conservators and professionals in the cultural heritage.

Cadmium yellows are a class of pigments based on cadmium sulfide (CdS) that can suffer degradation [1-4]. Although the degradation mechanism has been elucidated [5], the reasons behind the higher reactivity of some CdS are still unclear. It has been hypothesized that the higher reactivity can be related to an imperfect synthesis method [2-3]. This work shows that pigments synthesized following different routes [6-7] present different degrees of degradation in paints after artificial ageing. Moreover, the development of degradation products depends on the synthesis method and the photoluminescence emission from trap states [8] can be modified following degradation. Results obtained on in-laboratory prepared paints will be compared to historical degraded CdS paints from real paintings.

Increased availability and use of ‘non-invasive’ analytical techniques in recent years, have called into question traditional assumptions of non-invasiveness of laser-based techniques and latest research developments have shown that it is essential to assess the extent of it for Raman spectroscopy, as particular compounds such as pigments may be highly altered/damaged upon laser radiation even at low laser intensity. In the present research, damage processes of oil paintings with historical pigments under CW lasers, with different excitation wavelength, laser intensity and fluence, are investigated with a monitoring set-up combining Raman spectroscopy, VIS-NIR reflectance spectroscopy and IR thermography.

Removal of old deteriorated varnish layers from an easel painting is one of the most common but also most delicate restoration treatments. Apart from purely mechanical methods various solvents or mixtures of solvents have been used for this task over the last hundred years. Most often these chemicals were applied mechanically by swabbing, but also in a form of gels. However, the resulting formation of secondary and detrimental effects (such as swelling, leaching, solvent retention as well as high toxicity to the user) forced the development of new cleaning methodologies, aimed to overcome these drawbacks, guaranteeing a safe and effective removal of the damaged material. The aim of this paper is to discuss the applicability of optical coherence tomography for a multi-faceted and complementary assessment of different varnish removal processes, including the application of a novel nanogel system, the PHB-GVL. Since some effects, like swelling, may develop in a time span of hours, which is not a typical examination time for OCT, long-lasting stability of the measurement system had been ensured. For this task, a lab-developed high-resolution OCT instrument (3 µm axial resolution in the air) was adopted and the repeatability of surface recognition of 1.5 μm over 17 hours was achieved. This permitted for tracing of swelling effects in a multi-hour scale. The most desirable effect of such a restoration treatment is the removal of varnish without any alteration to the paint layer underneath. With the use of OCT, it was possible to trace this process by a direct comparison of the topography of the paint layer under varnish (before treatment) and after treatment. The results pointing at superior properties of the PHB-GVL nanogel applied with an electrospun polymeric tissue will be presented.

The potential of Optical Coherence Tomography (OCT) as an online monitoring tool for the conservation treatment of artworks and historical objects is well recognised. OCT gives non-invasive micron scale measurements on the stratigraphy of transparent and turbid multi-layered structures such as the paint and varnish layers on Old Master Paintings, enabling the monitoring of the removal of degraded varnish coatings during the cleaning process. In previous work we highlighted the difficulties in distinguishing glaze layers on paintings (coloured, translucent layers containing pigments with refractive indices very close to the binding medium) from those of aged varnish due to similarities in their scattering properties which gave similar appearance in OCT images. We proposed a method to extract the spectra from the translucent layers to distinguish the glazed layer from the varnish layers, mitigating the possibility of accidental removal of glaze layers by over-cleaning. The method extracts the spectral features of a semi-transparent layer using a combination of spectral imaging (400-850 nm) and OCT images from a region with relatively uniform paint composition. The OCT image cube provides the thickness measure of the translucent layers and when coupled with the knowledge of the spectral information of the surface layer, the aged varnishes and glaze layers could be distinguished. This method, however, relied on the accurate alignment of the two separate imaging systems with vastly different spatial resolutions which makes spatial registration difficult, affecting the crucial correlation between the spectra and layer thickness. In this work, we propose a combined multimodal instrument that collects both the spectral image and OCT images from the same region of a painting through the same objective. A number of design options are considered based on the modification of an in-house developed high-resolution OCT system. Preliminary proof of concept results is demonstrated on painting mock-ups.

The visual appearance of a painting is the result of variations in pigments, layers and layer thicknesses. An important role can be played by ground colour. The ground is the first preparation of the support before the actual painting. Medieval painters worked on white grounds. Coloured grounds appeared during the late 15th century in Italy before spreading to the northern part of Europe around 1550. Painters like Rembrandt or Rubens exploited dark or light coloured grounds to create spectacular, realistic effects. But how can we understand how they do this? To answer this question and add some quantifiable analysis, one needs to resolve the spectral reflectivity profile of a painting in three spatial dimensions. In addition, as the main intent is to relate the optical effects with colours, one needs to operate using visible light. The answer to these challenges is visible-light Optical Coherence Tomography (vis-OCT). In this study, we investigate the use of vis-OCT to measure the reflectivity profile of multi-layered paint samples in three dimensions. Using mock-up paint samples we prepared with two thin paint layers on a black and a white paper support, we measured the reflectivity profiles of the separate colours and of the superposed colours over either the black or white (back)ground. This paper first describes the signal processing involved in rebuilding the spectral reflectivity in three dimensions. Secondly, we will present the results obtained from the mock-up samples and draw conclusions on the possibility to discriminate colours in a three-dimensional context. All reflectivity measurements will be compared to a classical, commercially available hyperspectral imaging setup. This study is executed in the context of the NWO Down to the Ground Project. The results of the OCT measurements will be used by technical art historians and conservators for investigations into coloured grounds.

The results of research of porcelain art objects with overglaze and underglaze painting as well as colored glass objects are considered. The investigations were carried out by means of optical coherence microscopy method. Examples of diagnosis of porcelain, pigment and glaze layers in the near-infrared spectral range (1305±15 nm) with a resolution of about 10 μm are presented. The model approximations are considered in the study of multilayer structures in the near-surface area of art objects implemented using different materials.

X-ray computed-tomography is an established inspection technique for cultural heritage objects, but it is rarely used for painted micro-samples. These small, delicate, and complex parts of historical objects offer important and unique insights to conservators and restorers, but there is no standard method for preparing them nondestructively and without contamination. Synchrotron computed tomography provides sufficient resolution to analyze them, but it is an expensive and time-demanding technique. In contrast, laboratory high resolution computed tomography, which offers comparable spatial resolution, is relatively accessible, making it an effective tool for the analysis of such samples. This work presents a comprehensive methodology developed specifically for analyzing painted samples using high resolution computed tomography, demonstrating the overall capabilities of this method in the field of cultural heritage. The preparation of the sample, the measurement and the post-processing were optimized with new dedicated designs and methodology. The result was then analyzed, identifying visible features including grains, material density, layering, and strand. High resolution computed tomography provides sufficient quality of measurements for good interpretative studies, and the workflow presented here makes data acquisition and processing quick and easy while emphasizing conservation of the micro-sample. The resulting dataset is also an invaluable contribution to museum archives, and it can serve as a basis for further experiments.

This present collaborative research, undertaken in two different hemispheres, in an effort to address the challenge of early structural and sub-surface assessment of heritage marble architectures, like the Taj Mahal, using two complementary non-contact, non-invasive imaging techniques in the THz spectral range. In our previous work, it was already demonstrated that the complementary techniques of broadband Terahertz Time Domain Imaging (THz-TDI) and microRaman spectroscopy are successful in probing volume and surface damage in marble with Pietra-dura work. In the present work, the unique combination of THz-TDI and highly sensitive THz-Laser Feedback Interferometry (THz-LFI) have been explored to study sub-surface damage and irregularities of marble structures with Pietra-dura motif. These optical techniques hold immense possibility in large-scale architectural restoration projects as they collectively provide accurate structural depth profile up to several inches into the volume of the marble including the strain generated within the structure leading to potential cracks.

Studies of wall paintings require in situ ground based remote sensing evaluation. With its ablative nature, LIBS enables remote depth-resolved analysis. Combined with other remote technique s such as Raman and LIF, remote depth-resolved multi-modal analysis is made possible. Here we present a mobile standoff LIBS-Raman system with co-axial design. Other remote methods such as spectral imaging and LIF could also be incorporated, providing complementary information. Applications of standoff depth-resolved multi-modal material identification of wall paintings are demonstrated both in the lab and in situ for the first time, which helps better understand the painting schemes, and therefore inform decision-making for future conservation campaigns.

Historical buildings are prone to deterioration due to various reasons including environmental conditions, humidity and structural failures. The main factors of their degradation are moisture and salt activity. Salt weathering affects the appearance of the monuments but also causes chemical and mechanical degradation. The effect of salts in building deterioration is well-known, with several laboratory-based studies focusing on understanding the formation mechanisms. Here, we introduce a new methodology for the non-invasive monitoring and identification of moisture and salts following a complementary remote sensing approach. The study is based on ground-based remote short-wave infrared (SWIR) imaging and remote Raman spectroscopy from standoff distances of 3 to 15m [1]. The remote SWIR spectral imaging system covers the spectral range between 1 and 2.5 μm, with a spectral resolution of 5.5 nm and spatial resolution of 150 μm at a distance of 3m. The in-house developed mobile standoff Raman system operates with a continuous-wave (CW) excitation laser source at 780 nm. The laser beam can be focused at different distances resulting in a spot size of ~1 mm on the target. In our approach, SWIR imaging is used for scanning large wall surfaces. The post-processing of the acquired spectral imaging data using our novel machine learning-based clustering methods highlights the material variations across the wall. The detailed examination of the mean SWIR spectra for each cluster, allows a primary identification of moisture and salts, indicating also variations in volume concentration. The salts identification is then confirmed by remote Raman spectroscopy. The new method is presented through the examination of the historical building in Fort Brockhurst, an English Heritage monument in Portsmouth, UK.

This work introduces a novel fast hyperspectral image deblurring and denoising approach tailored to archaeological applications of remote sensing. Hyperspectral data recorded by means of airborne or satelliteborne sensors can be used to detect buried archaeological deposits as the latter have a localised impact on the physical and chemical properties of the soil and the vegetation located above them, contributing to make them structurally different from the surrounding elements. By processing and analysing hyperspectral images, archaeological photo-interpreters can detect subtle changes in the properties of ground elements that can be attributed to the presence of subterranean archaeological sites. Hyperspectral imagery, while rich in content as far as the spectral characteristics of ground elements, often lacks in spatial resolution and contains blurring degradation and noise, prominent especially in some spectral regions. The influence of blur and noise highly effects not only the quality of the visual appearance of the represented objects and compromises the interpretation process, but impacts also further processing of imagery, limiting consequently the detection of targets of interest. The methodology here presented is based on the low-rank properties of hyperspectral images and fully exploits a sparse hyperspectral data representation linked with the self-similarity characteristics of image patches (small image parts). The restoration procedure additionally includes a bend-dependent formulation of blurring degradation. The preliminary results show high performances and reduced computational complexity, and that the proposed approach is able to cope with Gaussian and Poisson noise and band-dependent blur. By removing severe noise and blur, the accurate detection and interpretation of buried structures in different shapes and sizes is thus improved. The proposed approach significantly increases the number of hyperspectral bands that can be used for further image processing and analysis, providing new avenues for features of interest discoveries in bands where they normally obscured by noise.

Carbon content is one of the most influential factors of the mechanical behavior of iron and steel and a time marker of the fabrication period. The quantitative assessment of carbon content distribution in archaeological artefacts gives us insights on their properties and nature. We performed micro-LIBS analysis on archaeological steel in order to reconstruct its carbon content distribution map. The quantitative mapping of the carbon distribution enabled us to infer the different phases of the metallographic structure without time-consuming Nital attack treatment. In addition, LIBS carbon content mapping revealed phases that are invisible with metallographic method.

The digital reproduction of a historical motion picture should resemble as much as possible the analog film projection at the time of the movie release. Nowadays, practices of capturing digital images of films do not properly consider the fundamental elements and conditions of the original film projection. The typical rigid three-band (RGB) capture cannot adapt to the multitude of historical color film stocks to be digitized, and the diffuse illumination on the film generally used by standard digital scanning devices is unable to guarantee the proper visual rendition of the original analog projection of film prints. In order to overcome these problems, we designed and built a novel multispectral imaging system that illuminates the film with a condensed light beam. The new imaging system and the computational pipeline were tested on an assorted set of photographic colors. The accuracy of the multispectral captures was tested by comparison with corresponding spectrally resolved point-based radiometric measurements of the light reflected by a screen during analog projection. The presented optical design represents an excellent solution for the creation of a new multispectral motion picture scanner prototype. The LED-based illumination system coupled with a film transport mechanism can be the core concept of a promising new generation of motion picture film scanners.

Infrared methods are of great importance in nondestructive testing of artworks, allowing a remote and wide-field imaging of interesting hidden features. Here we discuss a workflow based on thermal imaging in the mid infrared 3-5 micron range for the evaluation of subsurface defects in frescoes. Particular attention is payed to obtaining a high resolution (submillimetric) localization of the defects. The transfer of diagnostics techniques into real world applications, is discussed through the proof of concept of the proposed workflow on frescoes at the Sforza Castle (Milan, Italy).

Advanced nonlinear optical (NLO) microscopy enables quantitative in situ mapping of parchment degradation at the micrometer scale. We show that measurements of the ratio of fluorescence over second harmonic generation (SHG) signals probes severe collagen degradation and could help to identify the parchments most at risk, close to the irreversible collagen denaturation into gelatin. Conversely, the anisotropy parameter obtained from polarization-resolved SHG measurements probes the earlier stages of degradation. This approach is first validated by comparing NLO quantitative parameters to thermal measurements by differential scanning calorimetry on artificially altered contemporary parchments. We then analyze invaluable parchments from the Middle Ages.

Study of Historical Glass Grisailles by Non-linear Optical Microscopy M. Oujja(a), F. Agua(b), M. Sanz(a,c), D. Morales-Martin(b), M. García-Heras(b), M.A. Villegas(b), M. Castillejo(a) (a) Instituto de Química Física Rocasolano (CSIC), C/ Serrano 119, 28006 Madrid, Spain (b) Instituto de Historia (CSIC), C/ Albasanz 26-28, 28037 Madrid, Spain (c) Departamento de Física Interdisciplinar, Facultad de Ciencias, Universidad Nacional de Educación a Distancia (UNED), Senda del Rey 9, 28040 Madrid, Spain. In this work, the characterization via the Nonlinear Optical Microscopy (NLOM) modality of Multi-Photon Excitation Fluorescence (MPEF) of grisaille paint layers on historical stained glasses from different chronology and provenance in Spain is presented. Complementary glass analysis of the pieces was carried out by applying Laser Induced Breakdown Spectroscopy (LIBS) and Laser Induced Fluorescence (LIF) techniques. The grisaille paint layers studied display sufficient degree of transparency at the wavelength of 800 nm of the excitation femtosecond laser and in the spectral range of the emitted multiphoton fluorescence, making possible the non-invasive determination of the thicknesses of the grisaille paint layers by MPEF in the reflection configuration. The thickness values obtained by MPEF, in the range of 25 to 80 microns, were compared with those retrieved through Field Emission Scanning Electron Microscopy-Energy Dispersive X-ray Spectrometry (FESEM-EDS) measurements, showing good consistency and agreement. These results serve to validate the MPEF modality of NLOM for the non-destructive study of grisaille layers on historical glass substrates. Acknowledgments: This research has been funded by the Spanish State Research Agency (AEI) through projects PID2019-104124RB-I00/AEI/10.13039/501100011033 and PID2019-104220RB-I00 / AEI /10.13039/501100011033, by project TOP Heritage-CM (S2018/NMT-4372) from Community of Madrid, by EU H2020 project IPERION HS (GA 871034) and supported by CSIC Interdisciplinary Platform “Open Heritage: Research and Society” (PTI-PAIS). The authors acknowledge professional support from the TechnoHeritage Network of Science and Technology for the Conservation of Cultural Heritage.

Limoges enamels along with a lot of glass-based objects suffer from deterioration that affects the condition, structure and longevity of the pieces affected. Understanding the mechanisms and causality of this deterioration can aid in conserving and preserving the wares in an optimal manner. Limoges enamels are composed of multiple layers of glass over a metal substrate, multiple colours and levels of opacity are used with gildings and paillons to create vibrancy and decoration within the artwork. A main concern is the exposure of the glassware to moisture and pollutants that can cause crizzling, cracking and spalling of the enamel and cause detrimental and irreversible damage. Detection and analysis of the moisture content, progression of the gel layer (a compositionally modified layer formed on the surface of the glass due to the attack from moisture or pollutants), and overall subsurface condition of the enamels can help give insight into the level of deterioration. Furthermore, some enamels and certain colours show worse levels of deterioration. Is this a product of the environmental conditions of storage or the composition of the enamels? Non-invasive analytical techniques are a priority in analysis of cultural objects; therefore, multiple non-invasive techniques were employed to survey and analyse eight Limoges enamels from the sixteenth century in the British Museum collection. These techniques were 810nm Ultra-High-Resolution Optical Coherence Tomography (UHR OCT), 400-2300nm Fibre Optical Reflectance Spectroscopy (FORS), X-Ray Fluorescence (XRF), VIS/NIR (400nm-850nm) spectral imaging (PRISMS) and Shortwave Infrared (1000 – 2500nm) spectral imaging (SWIR). UHR OCT images the structure and level of deterioration throughout the enamel by showing the extent of the gel layer in the glass, as well as the structure and condition throughout the top layer. SWIR can be used to give information on the level of hydration in the glass across the entire enamel, this is mapped in 2D over the entire enamel for analysis. XRF has been used widely in glass analysis and can help identify the composition of the glass. PRISMS results give information on the spectra in the visible/NIR region complementing elemental analysis by XRF, it is useful in this investigation as a standardised way to analyse spectra and categorise the spectra and colour of an enamel. By using a combination of all of these techniques, investigations were conducted to understand if there is a link between the composition and deterioration of the selected sixteenth century Limoges enamels. Results using the OCT and SWIR analytical techniques have already shown a strong link between the level of hydration and the level of structural deterioration in these Limoges enamels, further analysis showed there was a correlation between the depth of the gel layer and the level of hydration. Furthermore, when incorporating all the techniques, initial findings have shown interesting insights into how the composition can affect the deterioration of these enamels.

Reflectance imaging spectroscopy (RIS) from visible to short-wave infrared (400 to 2500 nm), also known as hyperspectral imaging, is becoming another more widely used technique for the non-invasive study of polychrome art objects such as paintings. RIS is one of the many non- invasive imaging techniques used during “Operation Night Watch”. “Operation Night Watch” is the largest research project ever started by the Rijksmuseum in Amsterdam, and has the goal to investigate the conservation history, current condition, painting technique and artists’ materials of the Rembrandt iconic masterpiece Night Watch (1642) a canvas painting 3.78 m by 4.53 m in size. Due to the large size of the painting and its historical importance, the research is realized inside of a glass chamber that had been built around the painting in the “Gallery of Honor” of the Rijksmuseum, in front of the visiting public. RIS on the Night Watch was performed using two different hyperspectral line scanning imaging spectrometers (VNIR 400 to 1000 nm, 2.5 nm and SWIR 900 to 2500 nm, 6 nm). The complete painting was being scanned at a spatial resolution of 0.2 mm. The cameras including their lighting systems are mounted a on novel 2-D scanning platform, which includes auto focus systems that kept the line-scanning hyperspectral cameras in focus during scanning. The RIS results combined with the other non-invasive imaging techniques provide an in-depth understanding of Rembrandt’s painting technique and the actual condition of the painting and will serve as a foundation for the conservation treatment proposal for the Night Watch.

Degradation of paper and the consequent loss of its chemical and mechanical properties has been studied for many decades. For conservators an understanding of the loss of mechanical properties of paper during degradation is highly relevant from a practical point of view. Considering the fibrous microstructure of paper, the mechanical properties of single cellulose fibers and their change in time has been of interest in paper degradation studies. With current advances in experimental micromechanics, the characterization of cellulose fibers is achievable at small scales and with very high accuracy. Such detailed analyses on naturally aged paper in combination with accelerated aging experiments lead to valuable insight in the degradation of paper. The current study represents a novel methodology for the accurate mechanical characterization of micro-scale fibers, such as cellulose fibers. To this end, in-situ mechanical tests are performed using high resolution optical profilometry (white light interferometry) in combination with Digital Image Correlation (DIC) to attain detailed strain measurements. Given the curly geometry of cellulose fibers, there is considerable out-of-plane deformation during a micro-tensile test, making is necessary to use profilometric images. An in-house built setup is used for application of micro-scale speckle pattern needed for DIC. Reliable evaluation of the cross-sectional area of fibers is attained by acquiring profilometric images of both the front and back sides of each fiber, using a mirror in a novel self-calibrating setup. Detailed analyses of the results from different samples show the accuracy and reliability of the measurements and the methodology. By these means, an accurate evaluation of the stiffness and strength of cellulose fibers is attained. Performing such measurements on cellulose fibers from aged papers is expected to result in better understanding of the effect of cellulose degradation on the mechanical properties of paper.

Fluorescence is a photoluminescence phenomenon where light is absorbed at lower wavelengths and re-emitted at longer wavelengths. For classic artworks, fluorescence gives useful information about varnish and retouches. At the same time, modern artworks may employ synthetic fluorescent pigments because of their special appearance properties, such as increased brightness and vividness provoked by self-luminescence. Hence, it is relevant to investigate the fluorescent signals of cultural heritage objects when studying their appearance. This work proposes a variant to Reflectance Transformation Imaging (RTI) technique, namely Fluorescence Transformation Imaging. Reflectance Transformation Imaging method outputs a single-camera multi-light image collection of a static scene, which can be used to model the reflectance of the scene as a polynomial of the illumination directions. Similarly, Fluorescence Transformation Imaging aims to model the fluorescent signal based on a series of images with fixed scene and viewpoint and varying incident light directions - what changes with respect to RTI is that the wavelength of incident light needs to be shorter than the sensing wavelength. In the literature, there are works that explore the isotropic property of fluorescence in low-dimension multi-light imagery methods (such as Photometric Stereo) to model the appearance of an object with a first-order polynomial. This is because in the fluorescent mode the object gets closer to a Lambertian surface than in the reflective mode where non-Lambertian effects such as highlights are more likely to appear. Nonetheless, this assumption stands for single-object scenes, with uniform albedo and convex geometries. When there are multiple fluorescent objects in the scene, with concavities and non-uniform fluorescent component, then the fluorescence can become secondary light to the object and create interreflections. This paper explores the Reflectance and Fluorescence Transformation Imaging methods and the resulting texture maps for appearance rendering of heterogeneous non-flat fluorescent objects.

This contribution presents some examples of the application of ultraviolet fluorescence (UVF) photography and photogrammetry on cultural heritage objects and paintings. The used approach is based on low-cost systems sustainable in terms of costs for restorers and conservators, but, at the same time, able to supply valid and relevant information for a better knowledge of the preservation state, of previous restoration interventions and of possible superimposed materials. This knowledge is fundamental for planning and addressing the restoration activities, such as cleaning and consolidation, in the most appropriate way as possible. Specific cases studies will be reported concerning large paintings and 3D objects. In the first case, it has been necessary to acquire several images by dividing the surface into various parts, as function of the dimensions of the investigated area, and then by using photogrammetric tools to recompose the images into a single one (orthophotomosaic of the painting). In the second case, the UVF images are acquired all around the 3D objects and then processed in order to obtain a photorealistic model under ultraviolet fluorescence. The image acquisitions were obtained by using a digital camera equipped with different lens and filters. Lighting of the surfaces was obtained by UV projectors. The acquired images have been then processed through photogrammetric tools in order to obtain the final 2D and 3D ultraviolet fluorescence outputs of the investigated artworks that can be explored and profitably used for gathering metrically precise information and material response to UV radiation.

Digital image correlation (DIC) is a well-established technique for the measurement and monitoring of displacements and strains in engineering objects. In technical applications, an object's surface is modified by applying random, artificial structure, and monochrome cameras are typically used. The challenge in the measurement of Cultural Heritage objects (CHO) lies in the necessity of using the natural surface texture (no modifications are allowed), which in most of the cases is far from the ideal random pattern required for the successful implementation of DIC. On the other hand, spectrally separated content of natural CHO textures may provide additional spatial information and support DIC analysis. In this work, we propose a colour image pre-processing path that provides the input data best fitted to high accuracy 2D DIC and 3D DIC analysis. For this task we employ cameras with a colour filter array (CFA) with a Bayer pattern. This pattern has twice the number of green photosites as red or blue arranged in a 2x2pixel repeating-unit. From this sparse colour sampling, a full colour image is produced by interpolating the unknown values in each color channel. The interpolation is achieved via any one of the many demosaicing algorithms available to calculate a red, green, and blue value for every pixel position that only data from one channel was captured. These three R, G, B channels can then be combined to create a monochrome image suitable for conventional DIC analysis. This work's main objective is to select the best demosaicing algorithms for the spectral and monochromatic channels to minimize displacement and strain reconstruction errors (STD and P/V). The systematic analysis will be performed for objects (mock-ups) with artificial texture and fully controlled displacements. The expected errors due to interpolation procedures will be identified. Next, the best demosaicing procedure will be implemented into the full processing path of colour DIC used for selected CHO with natural texture (parchments, oil paintings). The analysis results based on monochrome, spectral, and mixed spectral data channels will be compared from the point of view of their applicability to different types of natural texture and achieved measurement accuracy.

The present work shows on the application of a terrestrial laser scanner (TLS) for the documentation of an interesting religious building preserved in the medieval archaeological site of Motta Sant’Agata, located in the hinterland of the Municipality of Reggio C., Italy. The survey project, part of the POR project “Circuito delle aree archeologiche urbane di Reggio Calabria”, has a twofold objective: 1. to create a 3D model with high resolution and metric accuracy for needs related to conservation, restoration and monitoring of degradation processes of the structures; 2. to develop digital products and media for dissemination and remote visit (via virtual tour and augmented reality). Considering the size of the area (about 900 mq) and the architectural features of the ruins, made up by perimeter walls of 30 m x 10m preserved for over 2 m in elevation, 4 underground crypts and other annexed structures (e.g. bell tower), the use of the Faro Focus 3D S120 appeared the most suitable choice. It is a portable and versatile laser-scanner, based on phase-shift technology, which is mounted on a tripod and is equipped with a calibrated RGB camera with 70 megapixels. This device has allowed to capture the entire religious complex through 94 positions of scans distributed along the nave, inside the crypts and along the perimeter walls. The model resulting from the scan process have finally provided a 3D digital replica, from which qualitative and quantitative information useful can be extracted: geometric measures, plans at different altitude, transversal and longitudinal sections and wall elevations. A virtual tour was also generated using the 360° pictures captured during each scan. TLS have finally revealed useful for metric documentation, monitoring the conservation of the buildings, as basis for digital or physical restoration as well for their enhancement and dissemination.

The technical photography (TP) method has been using in identifying pigments in paintings and the results could be used in the early stage before confirming with other methods such as X-Ray Fluorescence and Raman spectroscopy. The TP method employs visible, UV and IR as light sources with different filters. Moreover, the multi-spectrum method, using a continuous light source and various filters, has been used in the same application. This research proposed a method of using narrow multi-colored LEDs as light sources instead of colored filters. It aimed to optimize the number of LED channels for identifying pigments in conservation and restoration applications. Twelve tunable single-wavelength LEDs having wavelengths of 400-700 nm and 2 white LEDs, were used as light sources for capturing images of 357 Kremer pigments, applied on white card paper, without an optical brightening agent, through a visible pass filter, located in front of the single lens reflex Canon 5D Mark II camera that was modified by removing the UV and IR blocks. The 357 pigments including 9 main colors: 50 red pigments, 37 orange pigments, 82 yellows, 38 greens, 38 blues, 17 purples, and a group of greys browns, blacks and whites were used as samples. Subsequently, the pigments were classified, based on the captured images obtained from the individual LED. The redundancy of the CIEL*C*h data of each LED was reduced using the principal component analysis and the number of LEDs was optimized. It was found that all pigments could be classified and some pigments could be identified using single wavelength LEDs. The PCA should be applied to the CIEL*C*h data of pigments having similar shade. The 598 nm 425 nm LEDs were optimized for identifying and classifying blue pigments. The 430 nm, 640 nm and 540 nm were for purple, 403 nm, 540 nm, 660 nm and 672 nm for red, 403 nm, 447 nm, 540 nm and 672 nm for orange, 503 nm, 540 nm and 598 nm for yellow, 503 nm, 598 nm and 640 nm for green and 403 nm, 503 nm, 540 nm and 660 nm for a group of white, grey, black and brown.

Hyperspectral imaging (HSI) is a novel non-invasive analytical technique based on spectroscopy. It measures the light spectrum from each point of a scene of interest. It generates an accurate digital record for documentation and archiving in art conservation. This information can be used for diagnostics by monitoring changes, degradation or damages to paintings, for supporting in artwork restoration, for artist's material identification and pigment mapping, as well as for discovering the history of a piece of art by e.g. revealing underdrawings and retouchings. HSI measures the continuous spectrum of the light as a function of the wavelength λ for each pixel of the scene at coordinates (x, y) with fine spectral resolution, thus building the so-called 3-dimensional hyperspectral image. This data cube contains an extensive amount of information. Therefore, many numerical methods and algorithms have been developed to enable the extraction of quantitative parameters related to the physicochemical properties of the imaged objects from congested scenes. Here we present HERA, a novel and compact hyperspectral camera by NIREOS. The device, based on the Fourier-transform approach, combines high delay precision, long-term stability, insensitivity to vibrations and broad spectral coverage. It can measure absolute reflectance and fluorescence with very high spectral accuracy and resolution (≈3-nm, comparable to best commercial push-room systems) in the visible and near-infrared. HERA does not require any scanning of the object under analysis. This feature makes it extremely flexible and applicable to the study of works of art of different nature and size. Potential applications range from the on-site study of museum paintings, to the assessment of the conservation status of large monuments and historic buildings, to the documentation of small objects using standard macro photography lenses. In this paper, we will present a series of application examples in the field of conservation science to demonstrate its versatility.

During 15th and 16th centuries, while painters in Flanders or Italy used chalk (calcium carbonate) in ground layers of panel paintings, artists in Spain employed gypsum (calcium sulphate dihydrate). Thereby, the identification of these minerals in such artworks is relevant for historical studies, especially for that period owing to the active artistic exchange. Visible and near-infrared reflectance imaging spectroscopy is already applied to characterize pigments and binders. Besides, there are investigations suggesting that, owing to the transparency of some pigments mixed with binder in the near-infrared range, the signal coming from the subjacent substrate may be detected. This work proposes a methodology involving near-infrared reflectance imaging spectroscopy, for distinguishing between chalk- and gypsum-based ground layers. The methodology has been validated using reference samples of oil pigments applied on both preparation layers. Spectra of them reveal the distortions on the reflectance curves of pigments due to the ground layers. The hyperspectral images have been acquired with the VARIM 2.0 system, endowed with an InGaAs detector camera, coupled to an image spectrograph, covering the range 900-1700 nm. Several real cases have been examined. Study areas takes into account zones affected by retouching, rectifications and conservative interventions, previously identified by imaging techniques. The results prove the capability to discriminate gypsum and chalk on ground layers of panel paintings using a noninvasive methodology that involves near-infrared reflectance imaging spectroscopy and without sampling. Consequently, this technique can be a new tool to study the provenance of panel paintings from the 15th and 16th centuries.

Hyperspectral imaging has become a powerful technique for the non-invasive investigation of works of art. An advantage of this technique is the possibility to obtain spectral information over the entire spatial region of interest, allowing the identification and mapping of the constituent materials of the artefact under study. While hyperspectral imaging has been extensively used for artworks such as paintings and manuscripts, few works have been published on the use of this technique on stained glass. In this paper, a workflow for the imaging and analysis of stained-glass windows is proposed. The acquisition is carried out using a laboratory set-up adapted for transmittance measurement, which can support panels with a maximum size of around 50 x 50 cm. The image processing is carried out with two aims: visualization and chromophore identification. The results of this processing provide a foundation to discuss the potential of hyperspectral imaging for the scientific analysis of stained-glass windows.

X-Rays are a non-destructive, element specific probe of great potential for cultural heritage. Furthermore, synchrotron radiation sources provide high intensity leading to extraordinary sensitivity. These capabilities were exploited for studying four ancient gold coins dating back to the IV and V century A.D.. Combining the complementary information obtained by X-Ray Fluorescence and Photoemission Spectroscopy, we determined the chemical composition of the coins and we assess the speciation of the chemical contaminants providing information about historical situation of the minting period of the specimens and the metallurgic knowledge available at the time.

Optical Coherence Tomography (OCT) has proven to be an extremely valuable tool for the non-invasive stratigraphic analysis of paintings. One of the important components of OCT is the broadband laser source. The recent availability of off-the-shelf white light supercontinuum laser sources has meant that OCT systems can be built at any wavelength in the visible and short-wave infrared (SWIR) regime (~400-2500 nm). The most common OCT systems are those built for biomedical applications and they tend to be centered around near infrared spectral regions with low water absorption coefficient, such as 800nm and 1300nm. Historic artist materials such as paints tend to be highly scattering which limits the OCT depth of penetration at these wavelengths. A systematic study was conducted on paint layers composed of common artist pigments in egg tempera and oil to explore the optimum spectral window for maximum depth of penetration for OCTs and found it to be around 2.2 µm over the VIS/SWIR range. An OCT system was then developed at 1960nm and demonstrated to provide superior depth of penetration compared with lower wavelength OCT systems for highly scattering paint and other materials. Recently, the development of broadband laser sources has been extended to the mid-IR region. Consequently, there has been a growing interest in developing OCT with ever longer wavelength, beyond the SWIR, in the hope to increase the depth of penetration even further. To explore this in the mid-IR spectral region, we collected the FTIR spectra of a large selection of paint materials prepared as paint outs in external reflection and transmission mode in the region 4000 - 400 cm-1 (2.5 - 25 µm). With this work, we aim to systematically explore whether by extending the wavelength of OCTs to the mid-IR region would allow deeper penetration into objects of interest for cultural heritage science. To explore this in the mid-IR spectral region, we collected the FTIR spectra of a selection of paint materials prepared as paint outs in external reflection, transreflection and transmission mode in the region 4000-400 cm-1 (2.5-25 µm). External reflection (ER)-FTIR spectroscopy is a suitable tool for the non-invasive chemical characterization of materials and presents significant advantages (no need of sampling and detection of combination/overtone bands) compared to the other collection modes [4]. However, its use is still limited as FTIR spectra collected in ER mode, particularly in specular geometry, are much more challenging to interpret compared to FTIR spectra collected in Attenuated Total Reflection (ATR) and transmission mode. This is due to strong distortions affecting fundamental IR bands of ER-FTIR spectra, which are a direct consequence of the reflection phenomenon for absorbing materials in mid-IR. Multiple factors affect the resulting ER-FTIR spectra, including the material refractive index, absorption coefficient, roughness of the surface and particle size. Hence, the same pigments in egg tempera and oil applied on different substrates as paint outs were measured. Finally, the FTIR spectra collected will be used to compile a spectral database of paint materials, which will contribute to the advancement of ER-FTIR spectroscopy for non-invasive chemical analysis of materials.