Object Detection Under Rainy Conditions for Autonomous Vehicles: A Review of State-of-the-Art and Emerging Techniques
Mazin Hnewa, Hayder Radha · IEEE Signal Processing Magazine · 2020
Advanced automotive active safety systems, in general, and autonomous vehicles, in particular, rely heavily on visual data to classify and localize objects, such as pedestrians, traffic signs and lights, and nearby cars, to help the corresponding vehicles maneuver safely in their environments. However, the performance of object detection methods could degrade rather significantly in challenging weather scenarios, including rainy conditions. Despite major advancements in the development of deraining approaches, the impact of rain on object detection has largely been understudied, especially in the context of autonomous driving.