Removal of rain in panorama images using GAN

Abstract

In recent years, as a kind of important sensor camera is introduced in many automobiles in the field of automated driving. In particular, the recognition accuracy of the camera is an important research issue that leads to the safety of both drivers and pedestrians. Furthermore, the degradation of recognition performance under hazardous conditions is a critical issue. The proposed method based on panorama images containing information from 360 ° directions in a single image. In this paper, we propose rainfall and raindrop removal model for panorama images in order to improve the recognition accuracy of panorama images in rainy condition. A traditional model dedicated to the condition of rainfall is trained on panorama images because the distortions specific to panorama images occur and the recognition accuracy decreases. Moreover, the proposed model is also verified with panorama images including water droplets. Finally, the proposed method is evaluated with panorama images including rainfall and raindrop with respect to PSNR and SSIM.