Single Image Haze Removal Using Dark Channel Saturation Priori Model and Non-linear Diffusion Patch Method

In this article, a simple and effective restoration-based haze-removal approach is proposed. This approach is based on refining the course transmission map further by a novel non-linear diffusion patch method. The robustness of the proposed method is validated using quantitative analysis and is compared with other approaches with standard performance metrics. This technique can handle illumination, preserve edges better and ensures the original color of the image is retained. It can be used in many systems for example in object detection and tracking in order to recognize active traffic participants clearly on the road. Other applications include remote sensing for weather prediction, smart cars for smooth navigation and consumer electronics for fault identification.