The contribution of VNIR and SWIR hyperspectral imaging to rock art studies: example of the Otello schematic rock art site (Saint-Rémy-de-Provence, Bouches-du-Rhône, France)

Abstract

This paper presents a methodological contribution to rock art archaeology by demonstrating the bene ts of hyperspectral imaging, a relatively new method, for the understanding of rock art sites. It illustrates the complementarity of VNIR hyperspectral imaging, applied in rare cases to rock archaeology, and SWIR hyperspectral imaging, implemented here for the rst time to a rock art panel. Applied to a schematic rock art site in southern France, the Otello rock shelter (Saint-Rémy-de-Provence, France), this method allowed the discovery of numerous new gures invisible to the naked eye or unsuspected after image enhancement with the DStretch plug-in of the Image J software, the individualisation of gures within complex superpositions as well as the discovery of gures covered by weathering products. Moreover, by conferring a spatial dimension to the analysis of pictorial matter, thus allowing a classi cation of pigments at the scale of the wall, hyperspectral imaging makes it possible to automatically isolate different paintings and to carry out objective groupings of gures on the basis of their composition.Finally, hyperspectral imaging allows us to precisely document, distinguish and characterise weathering products interacting with painted gures. For all of these reasons, this method appears essential to highlight the relative chronology and syntax of iconography, and consequently to understand its cognitive nature.

Color-based discrimination of color hues in rock paintings through Gaussian mixture models: a case study from Chomache site (Chile)

“…Existing literature on the digital analysis of rock paintings underscores the importance of developing straightforward methods that align with archaeologists' training [9]. While this approach may be agreeable, there are case studies whose complexity necessitates the design of ad hoc solutions.…”

“…Hyperspectral imagery is notably effective in rock art studies, as it discriminates pigments by analyzing reflectivity across wider spectra than visible light [5][6][7][8][9][10][11]. Nonetheless, RGB (Red, Green, Blue) digital imagery analysis is common in these studies.…”

“…Nonetheless, RGB (Red, Green, Blue) digital imagery analysis is common in these studies. Tools like DStretch simplify using statistical techniques with minimal input [8][9][10], while fulfilling the needs of most archaeologists for digital image analysis. Additionally, computing implementation of statistic techniques, such as Principal Component Analysis (PCA) or Independent Component Analysis (ICA), have been explored, showing effectiveness in separating color tones [12][13][14][15], though they come with inherent limitations.…”