Adverse driving conditions like darkness, rain, and fog present significant challenges to professional drivers as well as to computer vision algorithms in autonomous vehicles. One potential solution is to use an on-board system for real-time image translation, transforming weather-affected images into clear ones.
Remote imaging systems raise unprecedented challenges in artificial intelligence. The dataset provided (extracted from the SpaceNet 6 challenge) shows SAR images having distorted intensities (compared to the expected results, the latter being visible in the RGB and NIR images which are also provided) due to the geophysics of the SAR acquisition system and the geometries of ground objects. Can we teach an Artificial Intelligence to find the right re-projections for automatically correcting such distorted and compressed intensities ?
