Title: Bilateral filter-oriented multi-scale CNN fusion model for single image dehazing

Authors: Jiangjiang Li; Jianjun Zhu; Huili Chen

Addresses: School of Electrical Engineering, Zhengzhou University of Science and Technology, Zhengzhou 450064, China ' School of Electrical Engineering, Zhengzhou University of Science and Technology, Zhengzhou 450064, China ' School of Electrical Engineering, Zhengzhou University of Science and Technology, Zhengzhou 450064, China

Abstract: This paper proposes a bilateral filter-oriented multi-scale CNN fusion model for single image dehazing. A multi-scale CNN model with low frequency and high frequency dehazing sub-network is designed. First, the haze image is decomposed by bilateral filter. The low and high frequency of haze image are obtained. Second, the map relationship between the high/low frequency and the high/low frequency transmittance is researched by the designed network model. Third, the high and low frequency transmittance obtained from the model is fused to obtain the scene transmittance map corresponding to the original haze image. Finally, according to the atmospheric scattering model, the haze image is restored to the clear image without haze, and the haze image data set is used to train and test the model. The experiment results show that the proposed method can achieve better dehazing effect in both subjective and objective evaluation.

Keywords: single image dehazing; bilateral filter; multi-scale CNN fusion; map relationship.

DOI: 10.1504/IJCVR.2023.129425

International Journal of Computational Vision and Robotics, 2023 Vol.13 No.2, pp.133 - 151

Received: 18 Dec 2021
Accepted: 29 Dec 2021
Published online: 09 Mar 2023 *

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