Image restoration and object detection in unfavourable weather conditions for autonomous vehicles using deep learning approaches: a review

Nowadays, autonomous vehicles are all the rage. Because of their capabilities, driverless vehicles have become very popular in recent years. Safety is the main priority in autonomous cars. It is crucial to be aware of what is going on around in order to give good safety. Autonomous vehicles rely on the visual information they are given to locate objects, identify lanes, to make decision, to recognise pedestrians, and detect traffic lights. However, in adverse weather conditions like rain, fog, dust, or cloudy conditions, the effectiveness of object detecting technologies may suffer very noticeably. Image restoration, which involves recovering latent clear images from damaged images, has recently attracted a lot of attention in a variety of restoration scenarios. In light of these, this study offers a thorough overview of object detection and picture restoration techniques for use in intelligent transportation systems on weather-damaged images.