Open AccessA Fast Image Dehazing Algorithm for Highway Tunnel Based on Artificial Multi-exposure Image Fusion
Author(s) -
Wenfeng Li,
Hongyan Wei,
Guanqiu Qi,
Hao Ding,
Ke Li
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/741/1/012038
Subject(s) - image fusion , computer science , visibility , artificial intelligence , image (mathematics) , computer vision , algorithm , fusion , filter (signal processing) , image restoration , composite image filter , image processing , optics , linguistics , philosophy , physics
Single image dehazing has been a challenging problem due to its ill-posed nature. This paper proposed a fast image dehazing algorithm for highway tunnel based on artificial multi-exposure image fusion. The original blurred images are transformed into under-exposed images using a series of gamma-correction operations. Meanwhile, a multi-exposure image fusion algorithm based on two-scale decomposition is proposed. It exploits the guided filter to separate each multi-exposure image into base and detail layers. The fused base and detail layers are integrated into the fused images. Then, a linear saturation adjustment method is utilized to enhance the saturation in spatial domain. Through the above image processing steps, the final haze-free images can be obtained. In this paper, the superiority of the proposed image dehazing algorithm based on artificial multi-exposure image fusion is demonstrated through theoretical analysis and experimental verification. It can quickly improve the visibility of foggy images, and make the processed images colorful and clear.