Image-based metric heritage modeling in the near-infrared spectrum

Digital photogrammetry and spectral imaging are widely used in heritage sciences towards the comprehensive recording, understanding, and protection of historical artifacts and artworks. The availability of consumer-grade modified cameras for spectral acquisition, as an alternative to expensive multispectral sensors and multi-sensor apparatuses, along with semi-automatic software implementations of Structure-from-Motion (SfM) and Multiple-View-Stereo (MVS) algorithms, has made more feasible than ever the combination of those techniques. In the research presented here, the authors assess image-based modeling from near-infrared (NIR) imagery acquired with modified consumer-grade cameras, with applications on tangible heritage. Three-dimensional (3D) meshes, textured with the non-visible data, are produced and evaluated. Specifically, metric evaluations are conducted through extensive comparisons with models produced with image-based modeling from visible (VIS) imagery and with structured light scanning, to check the accuracy of results. Furthermore, the authors observe and discuss, how the implemented NIR modeling approach, affects the surface of the reconstructed models, and may counteract specific problems which arise from lighting conditions during VIS acquisition. The radiometric properties of the produced results are evaluated, in comparison to the respective results in the visible spectrum, on the capacity to enhance observation towards the characterization of the surface and under-surface state of preservation, and consequently, to support conservation interventions.