Hyperspectral imaging is an emerging non-invasive method for the optical characterization of human skin, allowing detailed surface measurement over a large area. By providing the spectral reflectance in each pixel, it enables not only color simulation under various lighting conditions, but also the estimation of skin structure and composition. These parameters, which can be correlated to a person's health, are deduced from the spectral reflectance in each pixel thanks to optical models inversion. Such techniques are already available in 2D images for flat skin areas, but extending them to 3D is crucial to address large scale and complex shapes as in the human face. The requirements for accurate acquisition are a short acquisition time for in vivo applications and uniform lighting conditions to avoid shadowing. The proposed method combines wide field hyperspectral imaging and 3D surface acquisition, using a single camera, with an acquisition time of less than 5 seconds. Complete color consistency can be achieved by computationally correcting irradiance non-uniformities using 3D shape information.
Lou Gevaux, Cyprien Adnet, Pierre Séroul, Raphael Clerc, Alain Trémeau, Jean Luc Perrot, Mathieu Hébert, "Three-dimensional hyperspectral imaging: a new method for human face acquisition" in Proc. IS&T Int’l. Symp. on Electronic Imaging: Material Appearance, 2018, pp 152-1 - 152-10, https://doi.org/10.2352/ISSN.2470-1173.2018.8.MAAP-152