Title: A novel dual-fusion algorithm of single image dehazing based on anisotropic diffusion and Gaussian filter

Authors: Kaihan Xiao; Qingshan Tang; Si Liu; Sijie Li; Jiayi Huang; Tao Huang

Addresses: School of Physics and Electronic Science, Changsha University of Science and Technology, Changsha, China ' School of Physics and Electronic Science, Changsha University of Science and Technology, Changsha, China ' School of Physics and Electronic Science, Changsha University of Science and Technology, Changsha, China ' School of Physics and Electronic Science, Changsha University of Science and Technology, Changsha, China ' School of Computer Science and Information Engineering, Hubei University, Wuhan, China ' State-Owned Wuhan Changhong Machine Factory, Shidong Street, Wuchang District, Wuhan, China

Abstract: Dark channel prior (DCP) is a widely used method in single image dehazing technology. Here, we propose a novel dual-fusion algorithm of single image dehazing based on anisotropic diffusion and Gaussian filter to suppress the halo effect or colour distortion in traditional DCP algorithms. Anisotropic diffusion is used to edge-preserving smooth images and a Gaussian filter is to smooth the local white objects. A dual-fusion strategy is conducted to optimise the atmospheric veil. Besides, the fast explicit diffusion (FED) scheme is used to accelerate the numerical solution of the anisotropic diffusion to reduce time consumption. The subjective and objective evaluation of the experiment shows that the proposed algorithm can effectively suppress the halo effect and colour distortion, and has good dehazing performance on evaluation metrics. The proposed algorithm also reduces the time consumption by 54.2% than DCP with guided filter. This study provides an effective solution for single image dehazing.

Keywords: image dehazing; dark channel prior; DCP; anisotropic diffusion; fast explicit diffusion; FED; image fusion.

DOI: 10.1504/IJCSE.2023.129146

International Journal of Computational Science and Engineering, 2023 Vol.26 No.1, pp.54 - 64

Received: 11 Apr 2021
Accepted: 19 Oct 2021
Published online: 23 Feb 2023 *