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Open Access

An image dehazing method combining adaptive dual transmissions and scene depth variation

Lei LINYan YANG( )
School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
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Abstract

Aiming at the problems of imprecise transmission estimation and color cast in single image dehazing algorithms, an image dehazing method combining adaptive dual transmissions and scene depth variation is proposed. Firstly, a haze image is converted from RGB color space to Lab color space, morphological processing and filtering operation are performed on the luminance component, and the atmospheric light is estimated in combination with the maximum channel. Secondly, a Gaussian-logarithmic mapping of haze image is used to estimate the dark channel of haze-free image, and the bright channel of haze-free image is obtained by using the inequality relation of atmospheric scattering model. Thus, the dual transmissions are gotten. Finally, an adaptive transmission map with joint optimization of dual transmissions is constructed according to the relationship between depth map and transmission. A high-quality haze-free image can be directly recovered by using the proposed method with the atmospheric scattering model. The experiments show that the recovery results have natural color, thorough dehazing effect, rich detail information and high visual contrast. Meanwhile, good dehazing effects can be gotten in different scenes.

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Journal of Measurement Science and Instrumentation
Pages 413-424

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Cite this article:
LIN L, YANG Y. An image dehazing method combining adaptive dual transmissions and scene depth variation. Journal of Measurement Science and Instrumentation, 2023, 14(4): 413-424. https://doi.org/10.62756/jmsi.1674-8042.2023046

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Received: 18 February 2023
Published: 01 December 2023
© The Author(s) 2023.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.