Review on state of art image enhancement and restoration methods for a vision based driver assistance system with De-weathering

The mission of intelligent vehicles is to assist the driver in decision making. The researchers have paid attention on developing various driver assistance systems in order to assure road safety. Most of the driver assistance systems do not produce accurate results in poor weather conditions. Poor visibility is considered to be a main reason for accidents. When the weather is poor (haze, fog, darkness, snow etc...) the driver cannot get a clear view of the road. Images of outdoor scenes captured in bad weather are severely degraded. Most of the outdoor vision applications require robust detection of image features. The main aim of the paper is to review state-of-art image enhancement and restoration methods for a Vision based Driver Assistance System which will help the driver by providing a clear view of the road when the weather is bad. This process is called “De-weathering”. Reasons for degradation are explained in order to provide the scientific background of the problem. Various image enhancement methods are reviewed in this paper such as interactive de-weathering, de-weathering using multiple images, model based methods, non-model based methods and image de-noising, in order to find a suitable approach for the vision based driver assistance system.