Three-dimensional (3D) imaging and infrared (IR) thermography are powerful tools in many areas in engineering and sciences. Their joint use is of great interest in the buildings sector, allowing inspection and non-destructive testing of elements as well as an evaluation of the energy efficiency. When dealing with large and complex structures, as buildings (particularly historical) generally are, 3D thermography inspection is enhanced by Unmanned Aerial Vehicles (UAV—also known as drones). The aim of this paper is to propose a simple and cost-effective system for aerial 3D thermography of buildings. Special attention is thus payed to instrument and reconstruction software choice. After a very brief introduction to IR thermography for buildings and 3D thermography, the system is described. Some experimental results are given to validate the proposal.

Multispectral imaging (MSI) is a technique used to inspect materials properties in different domains, ranging from industrial to medical and cultural heritage and, recently, precision agriculture. Even though several MSI solutions are already commercially available, the research community is working to optimize multispectral cameras in terms of performance and cost. Systems for the agricultural field are usually very compact, combined with drones for large areas acquisition. In this work, we detail the implementation of an innovative, modular and low-cost solution of a multispectral camera based on three core camera systems in the optical (VIS–NIR) and thermal (LWIR) range. Multispectral imaging is performed with a rotating wheel of interchangeable band-pass filters. The system is also equipped with a set of environmental sensors to acquire CO₂ concentration values, light intensity, temperature, and relative humidity of the surrounding environment. The technology and the measurement protocol were experimentally validated in laboratory and in open field. Advantages with respect to the available MSI cameras mounted on UAV is the integrated imaging in both the reflectance and the thermal emissive band in a close-up imaging setup and the use of environmental sensors. From the multispectral stack the spectral signature of the plants can be obtained and various vegetation indices (e.g., NDVI, NDRE) can be calculated for investigating the health status of the plant, while thermography provide additional monitoring. Close-up multispectral imaging is expected to tackle the new challenges of precision agriculture by enabling the acquisition of high-quality dataset on single plants.

Dual mode imaging in the mid infrared band, a joint use of thermography and quasi-thermal reflectography, was recently proposed as a full field diagnostic tool in cultural heritage. Here we discuss for the first time, to the best of our knowledge, a detailed application of such non destructive technique to the diagnostics of frescoes, with an emphasis on the location of detachments. We also investigate the use of a thermographic method based on TSR (thermal signal reconstruction), in a long pulse stimulus scheme, as well as the spatial registration of thermal images after post-processing analysis to their visible counterpart, so as to obtain a fine resolution diagnostic map. As an exemplar case study, we report about the application of dual mode imaging with a 500 $${\upmu }\hbox {m}$$μ m pixel size at object plane on the “Monocromo”, a fresco by Leonardo da Vinci located in the Sforza Castle (Milan, Italy). Our technique was used to guide the conservators during the restoration works, opening new perspectives in artwork diagnostics.

Optical Coherence Tomography (OCT) is a relatively new medical imaging device that provides high-resolution and real-time visualization of biological tissues. Initially designed for ophthalmology, OCT is now being applied in other types of pathologies, like cancer diagnosis. This review highlights its impact on disease diagnosis, biopsy guidance, and treatment monitoring. Despite its advantages, OCT has limitations, particularly in tissue penetration and differentiating between malignant and benign lesions. To overcome these challenges, the integration of nanoparticles has emerged as a transformative approach, which significantly enhances contrast and tumor vascularization at the molecular level. Gold and superparamagnetic iron oxide nanoparticles, for instance, have demonstrated great potential in increasing OCT’s diagnostic accuracy through enhanced optical scattering and targeted biomarker detection. Beyond these innovations, integrating OCT with multimodal imaging methods, including magnetic resonance imaging (MRI), positron emission tomography (PET), and ultrasound, offers a more comprehensive approach to disease assessment, particularly in oncology. Additionally, advances in artificial intelligence (AI) and biosensors have further expanded OCT’s capabilities, enabling real-time tumor characterization and optimizing surgical precision. However, despite these advancements, clinical adoption still faces several hurdles. Issues related to nanoparticle biocompatibility, regulatory approvals, and standardization need to be addressed. Moving forward, research should focus on refining nanoparticle technology, improving AI-driven image analysis, and ensuring broader accessibility to OCT-guided diagnostics. By tackling these challenges, OCT could become an essential tool in precision medicine, facilitating early disease detection, real-time monitoring, and personalized treatment for improved patient outcomes.

The analysis of surface roughness in highly reflective metal artworks is challenging and requires contactless devices capable to measure regions with high micrometer accuracy in both depth and lateral directions. We demonstrate optical profilometry based on scanning conoscopic holography for micrometer measurement of silver samples treated with different hand-made cleaning processes. The technique is shown effective in acquiring shiny and smooth metal samples providing high-resolution and high-accurate dataset ( $$0.1\,\upmu \hbox {m}$$0.1 μ m depth and $$5\,\upmu \hbox {m}$$5 μ m lateral resolution) that is a reliable representation of the microsurface structure. From a statistical point of view, the cleaning treatments have the same nature of the low-abrasion, but the underlying mechanical processes are different. This fact suggested a more in-depth study of both the amplitude and the hybrid areal roughness parameters. It is proposed a workflow for a dual integrated multiscale roughness analysis for surface characterization: a scale inspection to detect possible texture non-homogeneity, and a signals separation to outline the most significant texture components. The scale-limited components allowed to discriminate the different surface processes. The results on silver samples demonstrate the potential of multiscale roughness analysis by conoscopic holography as a new tool for treatment monitoring in metal artworks.