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Open Access

Single image dehazing based on hazy features extraction and enhancement network

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

Convolutional neural network is developing rapidly in image processing. Most image dehazing algorithms only focus on dehazing but neglect the overall quality of dehazing image, which leads to problems such as loss of information blurred texture, etc. To solve these problems, we propose a dehazing and enhancement convolutional neural network. Hazy image and clear image are obtained by encoding and decoding. Enhancement network is used to restore the texture and details of dehazing image. Experiments show that the proposed method has excellent results in subjective evaluation and quality indexes. Haze can be removed more thoroughly, and images with clearer details and texture can be obtained.

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Journal of Measurement Science and Instrumentation
Pages 45-54

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Cite this article:
ZHANG J, YANG Y. Single image dehazing based on hazy features extraction and enhancement network. Journal of Measurement Science and Instrumentation, 2023, 14(1): 45-54. https://doi.org/10.62756/jmsi.1674-8042.2023006

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Received: 28 April 2021
Published: 01 March 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.