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In this paper, we discuss a new approach to the analysis of multi/hyper-spectral data sets, based on the Interesting Features Finder (IFF) method. The IFF is a simple algorithm recently proposed in the framework of Laser-Induced Breakdown Spectroscopy (LIBS) spectral analysis for detecting ‘interesting’ spectral features independently of the variance they represent in a set of spectra. To test the usefulness of this method to multispectral analysis, we show in this paper the results of its application on the recovery of a ‘lost’ painting from the Etruscan hypogeal tomb of the Volumni (3rd century BCE—1st century CE) in Perugia, Italy. The results obtained applying the IFF algorithm are compared with the results obtained by applying Blind Source Separation (BSS) techniques and Self-Organized Maps (SOM) to a multispectral set of 17 fluorescence and reflection images. From this comparison emerges the possibility of using the IFF algorithm to obtain rapidly and simultaneously, by varying a single parameter in a range from 0 to 1, several sets of elaborated images all containing the ‘interesting’ features and carrying information comparable to what could have been obtained by BSS and SOM, respectively.

L’impiego delle più sofisticate tecniche di rilevamento delle antiche pitture murali, mediante imaging multispettrali con analisi multivariate hanno consentito la restituzione e l’elaborazione grafica virtuale della decorazione pittorica murale della Tomba dei Demoni Azzurri (450–430 a.C.) della necropoli di Monterozzi, a Tarquinia (Viterbo, alto Lazio). È stato così possibile analizzare il programma iconografico originariamente concepito per la tomba, che comprendeva scene di caccia cui partecipavano prede autoctone e predatori esotici fra cui alcuni felidi vicino-orientali e/o nordafricani il cui uso come ausiliari venatori sarebbe qui documentato per la prima volta. The use of the most sophisticated techniques for the detection of ancient wall paintings, by means of multispectral imaging with multivariate analysis, has enabled the restitution and virtual graphic elaboration of the pictorial wall decoration of the Etruscan Tomba dei Demoni Azzurri (450-430 BCE) of the Monterozzi necropolis in Tarquinia (Viterbo, upper Latium). It was thus possible to analyse the iconographic programme originally conceived for the tomb, which included hunting scenes involving indigenous prey and exotic predators, including Near Eastern and/or North African felids whose use as hunting auxiliaries is documented here for the first time.

In this work, a critical review of the current nondestructive probing and image analysis approaches is presented, to revealing otherwise invisible or hardly discernible details in manuscripts and paintings relevant to cultural heritage and archaeology. Multispectral imaging, X-ray fluorescence, Laser-Induced Breakdown Spectroscopy, Raman spectroscopy and Thermography are considered, as techniques for acquiring images and spectral image sets; statistical methods for the analysis of these images are then discussed, including blind separation and false colour techniques. Several case studies are presented, with particular attention dedicated to the approaches that appear most promising for future applications. Some of the techniques described herein are likely to replace, in the near future, classical digital photography in the study of ancient manuscripts and paintings. Keywords: Image analysis, Cultural heritage, Archaeology, Multispectral imaging, Ancient manuscripts, Blind separation techniques

This paper aims to demonstrate the usefulness of digital reconstructions in the visualization and interpretation of analytical data obtained in science conservation projects. The study was carried out in the Tomb of the Monkey, one of the most important tomb of the Etruscan necropolis of Poggio Renzo, near Chiusi, dated around 480-470 BC. Photogrammetry survey method was used to generate a 3D model of the whole underground grave. The main advantage of this method, which is based on dense stereo matching tools, is the possibility to generate 3D reconstruction starting from a set of uncalibrated images, with non invasive and easy transportable hardware. Open source software is also used to integrate 3D wall painting data to the diagnostic researches: (I) Multispectral analysis, able to improve the readability of the painted scenes, detecting details otherwise invisible to the human eye, and (II) X-Ray Fluorescence data that give information on the elemental composition of materials and confirms the behavior of the multispectral signals collected on the wall painting surfaces.