Low-light image enhancement using gamma correction prior in mixed color spaces

• Published in: Pattern recognition Vol. 146; p. 110001
• Main Authors: Jeon, Jong Ju, Park, Jun Young, Eom, Il Kyu
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.02.2024
• Subjects: Atmospheric scattering model; Gamma correction prior; Inverted image; Low-light image enhancement; Mixed color spaces; Transmission map; Transmission map; Inverted image; Gamma correction prior; Mixed color spaces; Low-light image enhancement; Atmospheric scattering model
• ISSN: 0031-3203; 1873-5142
• DOI: 10.1016/j.patcog.2023.110001

In this paper, we propose an efficient and fast low-light image enhancement method using an atmospheric scattering model based on an inverted low-light image. The transmission map is derived as a function of two saturations of the original image in the two color spaces. Due to the difficulty in estimating the saturation of the original image, the transmission map is converted into a function of the average and maximum values of the original image. These two values are estimated from a given low-light image using the gamma correction prior. In addition, a pixel-adaptive gamma value determination algorithm is proposed to prevent under- or over-enhancement. The proposed algorithm is fast because it does not require the training or refinement process. The simulation results show that the proposed low-light enhancement scheme outperforms state-of-the-art approaches regarding both computational simplicity and enhancement efficiency. The code is available on https://github.com/TripleJ2543.