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Method for removing haze from images, captured under a wide range of lighting conditions
A.I. Filin 1, A.V. Kopylov 1, I.A. Gracheva 1

1 Laboratory of Cognitive Technologies and Simulation Systems,
Tula State University, 300012, Tula, Russia, Lenin ave. 92

 PDF, 1176 kB

DOI: 10.18287/2412-6179-CO-1361

Pages: 102-108.

Full text of article: English language.

Abstract:
The presence of haze on images degrades the quality of perception and automatic analysis of scenes. One of the most popular methods of haze removal is the dark channel prior method, which is based on the Koschmieder atmospheric scattering model. However, its underlying assumptions are not met for nighttime, since localized light sources make a significant, if not the main, contribution to lighting. We propose here to use the degree of belonging of an image element to a localized light source, determined based on a one-class classifier, as a value that characterizes the confidence of the corresponding element of the estimated transmission map during its rectifi-cation based on the gamma-normal model, which makes it possible to increase the accuracy of dehazing when processing images, captured in low-light or nighttime conditions.

Keywords:
haze removal, image restoration, dark channel prior, transmission map, point-light source, low-light conditions.

Citation:
Filin AI, Kopylov AV, Gracheva IA. Method for removing haze from images, captured under a wide range of lighting conditions. Computer Optics 2024; 48(1): 102-108. DOI: 10.18287/2412-6179-CO-1361.

Acknowledgements:
This research is funded by the Ministry of Science and Higher Education of the Russian Federation within the framework of the state task FEWG-2021-0012.

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