A Review on Image Enhancement Using Intelligent Transportation System

Enhancement plays an important role in digital image processing.The visibility of images of open air road scenes becomes degraded when captured in severe climate conditions. Drivers frequently turn on the headlights of their vehicles and streetlights are regularly actuated, bringing about confined light sources in images of road scenes in these conditions. Furthermore, dust storms are additionally climate occasions that are regularly experienced when driving in a few districts. A novel and effective haze removal approach to cure these issues created by confined light sources and color shifts, which subsequently accomplishes better restoration results for single hazy images. Poor visibility degrades quality and performance of computer vision algorithms for smart transportation frameworks, for example, traveling vehicle data recorders and traffic surveillance systems, activity observation frameworks which must operate under a wide range of weather conditions. Another issue is that the captured foggy road scene images contains confined light sources or shading movement issues because of dust storm conditions. Movement detection and Darkness are also problems in the captured images. The goal of this work is to enhance the road scene images using different filters and enhancement techniques. The distinctive sorts of parameters are figured that are PSNR, MD, MSE and Processing Speeds.