## 1 Introduction  
Understanding the features of an artifact's surface can enrich its analysis from various points of view, offering morphological, dimensional, and chromatic information, shedding light on the artifact's manufacturing process and facilitating the assessment of its conservation state. To this aim, several imaging techniques are employed in the cultural heritage documentation field. Among many, raking light finds great application, since it highlights details that are often difficult to see with the naked eye, thus serving as a complementary tool alongside the more traditional diffuse light and multiband imaging analysis [1]. Nowadays, the necessity of integrating different sources of data to achieve a more accurate and detailed reconstruction of an artifact's geometry and aspect is emerging, as highlighted by the application of imaging methodologies that are positioned at the intersection of the two-dimensional (2D) and three-dimensional (3D) worlds. For instance, Photometric Stereo and multi-light 3D surveying are examples of hybrid approaches that can be used to extract three-dimensional information from two-dimensional data [2]. Photometric Stereo is a widely used technique for evaluating the morphology of various subjects. It extracts 3D information from 2D data by varying the incidence of light on the subject, similarly to Reflectance Transformation Imaging (RTI) [2]. Another example of the hybrid approach is multi-light 3D surveying. This method combines close-range photogrammetry and multiband photography with variable incident light, resulting in a mosaic of enhanced orthographic images that enrich the knowledge of different materials and surface features [3,4]. Furthermore, the combination of 3D data obtained with different devices offers numerous opportunities for studying large-scale objects, for which close-range techniques would be neither practical nor feasible. Cartography and topography make increasing use of integrated data from total stations, laser scanners, Simultaneous Localization and Mapping systems (SLAM), and drone photogrammetry for surveying built environments [5,6]. Therefore, data fusion seems to be the most powerful approach to get the most out of each methodology, adapting the capture process to the contexts and the available equipment. An imaging technique that is continuously evolving to meet the demands of research in the cultural heritage field is RTI. The RTI method's popularity has led to the continuous development of tools and algorithms since its initial application [7]. RTI is a computational digital photography method for representing artifacts in two dimensions that is extensively utilized in the domain of cultural heritage imaging.It is a tool for visualizing and extracting morphological data from an object's surface using photographs [8, 9, 10, 11]. This approach accentuates the design, reflectivity, and structure of various artworks, such as coins [12], archaeological objects [13,14] or museum artefacts [12, 13, 14]. RTI is acquired using a stationary point camera, while the position of the light source is systematically adjusted by the operator prior to each image, following a predefined geometric scheme. The movement of the light source is arranged using a predefined geometric pattern, similar to the metal structure of an umbrella, yielding images ranging from raking (10\({}^{\circ}\)) to nadir lighting (90\({}^{\circ}\)), encompassing intermediate angles as well (30\({}^{\circ}\), 45\({}^{\circ}\), and 60\({}^{\circ}\)). The workflow of RTI starts with the photographic acquisition of the object under study. Initially, images undergo color balance and export, before undergoing processing in dedicated software. This may include Relight [15], which utilizes a black sphere to mark the position of the light source in space [16]. Generally, there are a few common ways to collect suitable images for RTI.