Title: A fast video haze removal algorithm via mixed transmissivity optimisation

Authors: Jianbo Xu; Nanjun Ma; Jian Ke; Eileen Jianxun Yang; Shu Feng

Addresses: School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan 411201, China ' School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan 411201, China ' School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan 411201, China ' Shenzhen Research Institute, Sun Yat-Sen University, Shenzhen 518057, China ' School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan 411201, China

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.

Keywords: dark channel prior; guided filter; median filter; digital webcam; video defogging.

DOI: 10.1504/IJES.2019.097574

International Journal of Embedded Systems, 2019 Vol.11 No.1, pp.84 - 93

Received: 13 Jul 2018
Accepted: 05 Aug 2018
Published online: 29 Jan 2019 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article