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yanshiju@usst.edu.cnThe mainstream defogging algorithms can be classified into three categories based on their principles: image enhancement-based, physical model-based, and neural network-based.
This paper aims to introduce and explore these categories, as well as to provide an outlook on the application and possible future development directions of defogging algorithms.
Open Accessyanshiju@usst.edu.cnThe mainstream defogging algorithms can be classified into three categories based on their principles: image enhancement-based, physical model-based, and neural network-based.
This paper aims to introduce and explore these categories, as well as to provide an outlook on the application and possible future development directions of defogging algorithms.
Images taken under hazy weather conditions suffer from problems such as blurring, low contrast, and low saturation due to the scattering of atmospheric light by aerosol particles in the air, which affects the performance and judgment of image analysis equipment. With the rapid development of image processing technology and computer vision technology, researchers have proposed a large number of targeted haze removal algorithms to improve the quality of images taken under hazy weather conditions. According to the haze removal principle, mainstream haze removal algorithms can be classified into three categories: image enhancement-based, physics model-based, and neural network-based. This paper introduces and explores classic haze removal algorithms from the perspectives of principles, development, advantages, and disadvantages, and outlines the prospects for the future development and application direction of haze removal algorithms.
ISSN: 2957-5478
Volume 1, Issue 2
September 2023
Pages: 55-130
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