Image Deraining and Denoising Convolutional Neural Network For Autonomous Driving

Perception plays an important role in reliable decision-making for autonomous vehicles. Over the last ten years, huge advances have been made in the field of perception. However, perception in extreme weather conditions is still a difficult problem, especially in rainy weather conditions. In order to improve the detection effect of road objects in rainy environments, we analyze the physical characteristics of the rain layer and propose a deraining and denoising convolutional neural network structure. Based on this network structure, we design ablation experiments and experiment results show that our method can effectively improve the accuracy of object detection in rainy conditions.