Real-time image and video dehazing based on multiscale guided filtering

• Published in: Multimedia tools and applications Vol. 81; no. 25; pp. 36567 - 36584
• Main Authors: Van Nguyen, Thuong, Vien, An Gia, Lee, Chul
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.10.2022; Springer Nature B.V
• Subjects: 1213: Computational Optimization and Applications for Heterogeneous Multimedia Data; Algorithms; Computer Communication Networks; Computer Science; Data Structures and Information Theory; Deep learning; Estimation; Image filters; Iterative methods; Light; Multimedia; Multimedia Information Systems; Real time; Special Purpose and Application-Based Systems; Video; Image dehazing; Guided image filtering; Image restoration; Image enhancement
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-022-13533-4

We propose a real-time dehazing algorithm for hazy images and videos based on multiscale guided filtering. The most time-consuming step in physical model-based algorithms is estimating the transmission map and atmospheric light. In this work, we develop a computationally efficient approach for the estimation. First, we construct an image pyramid from a hazy image. Then, we estimate the transmission map and atmospheric light at the coarsest level. Next, we obtain the transmission at the finest level by iterative upsampling with guide image filtering to avoid information loss. Furthermore, we extend the single-image dehazing algorithm to real-time video dehazing to reduce flickering artifacts in dehazed videos by making transmission values temporally coherent. Experimental results show that the proposed algorithm is applicable in real-time applications, while providing comparable or even better performance than that of state-of-the-art algorithms.