A Review of Foggy Image Enhancement for Autonomous Vehicles

Abstract- Foggy weather conditions significantly affect the performance of autonomous vehicles by reducing visibilityand affecting object detection accuracy. This literature review examines various image enhancement techniques designedto solve these challenges. Methods such as defog yolo, Dark Channel Prior, local atmospheric evil conclusions, andcyclegan-based fog removal shows significant improvements in image quality and object detection in foggy conditions.Future research should focus on improving algorithm efficiency to integrate, expand datasets and ensure safe autonomousdriving in various weather scenarios with real -time detection systems.