3D reconstruction has become a challenging task for navigation systems in recent years. Therefore, different technologies such as RGB cameras, LIDARs, or RADAR can capture information from the environment and perform the 3D reconstruction. However, in an environment of high dispersion and low illumination, it is necessary to have a robust solution that operates in the infrared spectrum. One solution is to integrate Single-Pixel Near Infra-Red Imaging (NIR-SPI) technology, allowing mage reconstruction of a few samples and operating high dispersion conditions. Using an SPI-NIR vision system with active illumination for 3D image reconstruction in rainy environments is a solution. The reconstruction of 3D objects is performed from their construction of a low-resolution SPI-NIR 2D image, using a robust unified reflectance model that combines the Lambertian, Oren-Nayar, and Blinn-Phong models to improve the 3D image of objects with surface roughness or with low reflectance. For 3D reconstruction, single-view Shape-From-Shading (SFS) based on fast Eikonal solvers was used. Which makes it possible to improve the shape of the 3D object, reduce computation time for future applications and generate real-time 3D images in harsh environments.
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