Low-light image enhancement using inverted image normalized by atmospheric light

•This paper presents a novel low-light image enhancement algorithm using the inverted image normalized by atmospheric light.•A mathematical connection between the Retinex theory and the atmospheric scattering model by normalizing an inverted image to atmospheric light is derived.•The medium transmission is derived as a function of the saturation of the scene radiance only, and the image-adaptive saturation of scene radiance is estimated via a simple stretch function according to the average saturation of the low-light image.•The proposed low-light image enhancement algorithm is fast because it requires no training, prior knowledge, or refinement.•The simulation results confirm that in terms of both computational complexity and enhancement efficiency, the proposed low-light enhancement scheme outperforms other state-of-the-art approaches.