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Open Access

Dehazing algorithm for adaptively corrected transmission under multi-scale morphology

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

In order to solve the problems of color bias and visual deviation caused by inaccurate estimation of transmittance and atmospheric light in image defogging, a new algorithm based on multi-scale morphological reconstruction with adaptive transmittance and atmospheric light correction was proposed. Firstly, the algorithm used the open operation under morphological reconstruction to replace the minimum filter operation in the dark channel, and used the morphological edge to set the scale of the open operation structure elements, and constructed a multi-scale open operation fusion dark channel. After morphological noise reduction, the exact initial transmittance was obtained. According to the relationship between brightness and saturation difference and transmittance, an adaptive transmittance correction model was fitted with Gaussian function to correct the initial transmittance of the sky fog map. Then the local atmospheric light was improved according to the image brightness information and morphology closure operation. Finally, the proposed algorithm was combined with the atmospheric scattering model to obtain an accurate fog free image. The experimental results showed that the proposed algorithm was suitable for fog image restoration under various scenes, the restoration effect was good, and the brightness was suitable.

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Journal of Measurement Science and Instrumentation
Pages 477-489

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Cite this article:
ZHANG S, YANG Y. Dehazing algorithm for adaptively corrected transmission under multi-scale morphology. Journal of Measurement Science and Instrumentation, 2024, 15(4): 477-489. https://doi.org/10.62756/jmsi.1674-8042.2024048

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Received: 15 May 2023
Revised: 03 July 2023
Accepted: 21 August 2023
Published: 01 December 2024
© The Author(s) 2024.

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.