This paper presents first laboratory results of a combined approach carried out by the use of three different portable non-invasive electromagnetic methods: Digital holographic speckle pattern interferometry (DHSPI), stimulated infrared thermography (SIRT) and holographic subsurface radar (HSR), proposed for the analysis of a custom-built wall mosaic model. The model reproduces a series of defects (e.g., cracks, voids, detachments), simulating common deteriorated, restored or reshuffled areas in wall mosaics. DHSPI and SIRT, already well known in the field of non-destructive (NDT) methods, are full-field contactless techniques, providing complementary information on the subsurface hidden discontinuities. The use of DHSPI, based on optical imaging and interferometry, provides remote control and visualization of surface micro-deformation after induced thermal stress, while the use of SIRT allows visualization of thermal energy diffusion in the surface upon the induced thermal stress. DHSPI and SIRT data are complemented by the use of HSR, a contact method that provides localized information about the distribution of contrasts in dielectric permittivity and related possible anomalies. The experimental results, made by the combined use of these methods to the identification of the known anomalies in the mosaic model, are presented and discussed here as a contribution in the development of an efficient non-invasive approach to the in-situ subsurface analysis of ancient wall mosaics.

This study presents a novel platform for the non-invasive analysis of painted surfaces, integrating sequentially shifted excitation (SSE ^TM ) Raman mapping with 3D scanning. Designed for hardware-registered data acquisition, the system enables automated macro-Raman mapping across extended and uneven surfaces with precise spatial control. To demonstrate the platform potential in accurate material mapping, we showcase the results acquired from purposely prepared acrylic mock-ups and a painting. The coupling of 3D surface information with subsequent Raman spectral acquisition was exploited for precise focus adjustment and co-registration of datasets. We demonstrate the potential of combined 3D and SSE ^TM Raman mapping—so far not implemented in cultural heritage contexts—for non-invasive analyses, even in scenarios with high fluorescent signals. The system’s modular design permits future integration of additional imaging modalities, making it a promising tool for advanced analysis in conservation science.

We present a custom platform for multimodal analysis that is currently integrating 3D scanning, Reflectance Imaging Spectroscopy (RIS) in the visible range (420–720 nm), and Sequentially Shifted Excitation macro-Raman mapping (SSE ^TM -MA-Raman) within a single, fully spatially hardware-registered framework. The system was conceived to overcome one of the major limitations in multimodal cultural heritage diagnostics: the difficulty of reliably registering Regions of Interest (ROIs) and aligning heterogeneous datasets acquired with independent instruments. The core of the platform is an optical breadboard, moved by a three-axis motorised stage with micrometric repeatability, and custom control software enabling automated acquisition, instrument synchronisation, and intrinsic spatial co-registration across modalities. Here, we describe the system architecture, the acquisition pipeline, and the Raman handshaking routine, demonstrating how the integration of topography-driven autofocusing with coordinated RIS and SSE ^TM -MA-Raman mapping enhances accuracy, reproducibility, and facilitates data interpretation. The potential and performance of the platform were evaluated on a real-case scenario: a contemporary painting by Gastone Novelli (1925–1968) from the Peggy Guggenheim collection (Venice, Italy), currently under restoration at the Opificio delle Pietre Dure (OPD) in Florence, Italy. The results confirm the strength of this new hardware-registered system as a robust solution for advanced multimodal investigations in heritage science, producing co-registered datasets containing complementary morphological and spectroscopic information.