A fast video haze removal algorithm via mixed transmissivity optimisation

Abstract

Image restoration is an important approach to image and video defogging. One of the most popular algorithms for image restoration is dark channel prior. However, when the algorithm is applied to outdoor digital webcams with limited computing resources, its real-time performance probably cannot be guaranteed. To address the above issue, this paper presents a fast video haze removal algorithm based on mixed optimised transmissivity to improve the time performance of the dark channel prior algorithm. The proposed algorithm combines guided filter and median filter and replaces the soft matting procedure in the classical dark channel prior algorithm. A set of experiments are performed to evaluate the real-time performance and effectiveness of the algorithm. The results show that our proposed improved algorithm can significantly improve the speed of video defogging, without sacrificing much effectiveness in identification of target objects.

RFID aided SINS integrated navigation system for lane applications

“…With the rapid development of precision positioning technology, the demand is becoming more and more obvious, the market is also growing, and the application occasions are also increasing (Wang et al, 2019). The most common navigation service can help people quickly make travel routes, greatly facilitating people's travel (Xu et al, 2019). To achieve these aims, the first step is to achieve real time precision positioning (RTPP).…”