DFOG-Image Processing Application for Real-Time Defogging

Abstract

The enhancement of real-time video taken under bad visibility or bad weather is a vital necessity in consumer transport industry and computer vision applications. During the past decade, many researchers have been devoted to the problem of how to remove fog noise from real-time video. Nowadays vehicle industry uses various computing systems to assist in the transport of travelers from one location to another .now most of the cars have revers camera front cameras and sensors who give the signal when the vehicle is near to another object. These detections and identification are useful for the safe operation of vehicles. When looking through vehicle accident history, many accidents caused bad weather conditions. Fog, haze, rain, and other natural weather conditions cannot remove physically. Fog and haze block vison above 1 kilometer. There is a defogger in the windscreen, but it is only removed Mist on the windscreen. For the driver's vision above the rode, there is no such thing for that. The purpose of this research paper is introducing a new system to remove fog from real-time video and give detailed visual to the driver in foggy or other bad weather condition. This D-Fog system includes functions such as give clear realtime visual in bad weather condition, recognize, and give details about the object above the road, give the distance between objects and vehicle. In this system, main function is producing real-time defogged, clear video. Combination of Ha and Hoon method and Dark channel priority method used to get this real-time defog video. To recognize the object, this system has use thermal sensors and heat maps. To get the distance between object and vehicle this system has use LIDAR sensors. Because of this facility, we can name this system as three in one system.