Abstract
Low-light image enhancement is still a challenging task nowadays. On one hand, sensitive methods tend to reproduce light images with severe noise and color deviation. On the other hand, insensitive methods can recover clear and natural results but with much lower brightness. Hence, this paper analyzes several basic mathematical models and then proposes a low-light image enhancement network (LLIENet) based on a basic mathematical model, which contains several modules. First, a MaskNet is proposed to estimate the global illumination prior. Second, BaseNet and CoefficientNet are used to decompose the low-light image into a lightened base image and a subtle coefficient map. Finally, a RefineNet is added to further refine high-frequency details and suppress noise and color deviation. Extensive experiments are evaluated to demonstrate the superiority of the proposed method over several state-of-the-art methods.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
