Abstract
Spectral imaging is a technique that captures spectral information from a scene and maps it onto a 2D image, featuring the potential to reveal hidden features and properties of objects that are invisible to the human eye, such as elemental and molecular compositions. Augmented reality (AR), on the other hand, is a technology that enhances the perception of reality by superimposing digital information on the physical world. While these technologies have different purposes, they can be considered one and the same in terms of providing an user-centric extension of reality. Spectral imaging provides the information that can reveal the underlying nature of objects, while AR provides the method of visualization that can display the information in an intuitive and interactive way. In this work, we present a novel Unity toolkit that combines spectral imaging and a HoloLens 2 AR device to create an interactive and immersive experience for the user. The toolkit enables the interactive visualization of various elemental maps of a 3D rock model in AR using a simple and intuitive interface. With this technique, the user can select a sample model and an elemental map from a preloaded asset library and then see the map projected onto the rock model in AR, using simple interactions such as zoom adjustment, rotation, and pan of the models to explore features and properties in detail. The toolkit offers several advantages, including better contextual interpretation of the spectral data by placing it in relation to the shape and texture of the rock, increased user engagement and curiosity through the creation of a realistic and immersive experience, and ease of decision-making through the provision of comparative tools. In short, by combining spectral imaging and AR, we present an innovative approach that can enrich the user experience and expand the user knowledge of the environment.

Abstract
Imaging the spatial distribution of chemical elements at a sample surface is a common application of laserinduced breakdown spectroscopy with vast scientific and technological applications. Yet, typical imaging solutions only explore the creation of two-dimensional maps, which can limit the interpretability of the results and further diagnostics in three-dimensional settings. Within this context, this work explores the combination of spectral imaging techniques and photogrammetry to deploy a versatile solution for the creation of threedimensional spectral imaging models. First, by making use of a numerical algorithm that is able to match features in the spectral image with those of the three-dimensional model, we show how to match the mesh from distinct sensor modalities. Then, we describe a possible visualization workflow, making use of dedicated photogrammetry and visualization software to easily deploy interactive models. Overall, the results demonstrate the versatility of our approach and pave for the development of novel spectral imaging diagnostic strategies that are able to deliver better qualitative analysis and insight in the three-dimensional space.