A zero-reference nighttime road image enhancement method

The majority of existing low-light image enhancement methods are based on uniform low illumination, they are prone to issues such as overexposure, dark area noise amplification, when applied to nighttime road images with various lighting and high noise levels. This paper proposes a zero-reference two-stage nighttime road image enhancement method. In the first stage, a lightweight visual attention network (LVAN) is developed to generate the dark-aware attention map, effectively avoiding the problems of overexposure and underexposure. The second stage is enhanced with a zero-reference depth image enhancement network in CIELab color space (ZeroDIE_Lab), which enhance image brightness significantly, suppresses noise and artefacts effectively while maintaining color consistency. In comparison with established low-light image enhancement approaches, such as Zero-DCE, the experimental results demonstrate that the proposed method not only enhances the visual clarity and structural details of the image, but also exhibits notable advantages in quantitative evaluation metrics, including image quality assessment and computational complex.