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

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.

Automated summary

In this paper, an efficient and fast low-light image enhancement method is proposed using an atmospheric scattering model based on an inverted low-light image. The transmission map is derived as a function of the average and maximum values of the original image, and a pixel-adaptive gamma value determination algorithm is used to prevent under- or over-enhancement. The proposed method is computationally simple and outperforms existing approaches in terms of enhancement efficiency.