Let the sunshine in: Sun glare detection on automotive surround-view cameras

Abstract

Sun glare is a commonly encountered problem in both manual and automated driving. Sun glare causes over-exposure in the image and significantly impacts visual perception algorithms. For higher levels of automated driving, it is essential for the system to understand that there is sun glare which can cause system degradation. There is very limited literature on detecting sun glare for automated driving. It is primarily based on finding saturated brightness areas and extracting regions via image processing heuristics. From the perspective of a safety system, it is necessary to have a highly robust algorithm. Thus we designed two complementary algorithms using classical image processing techniques and CNN which can learn global context. We also discuss how sun glare detection algorithm will efficiently fit into a typical automated driving system. As there is no public dataset, we created our own and will release it publicly via theWoodScape project to encourage further research in this area.