Abstract
Low light image enhancement plays the crucial role in night vision applications, and road monitoring systems of artificial intelligence assisted vehicles. But the conventional methods are unable to remove the darkness from source images and resulted in poor visibility performance. Thus, this article proposed an advanced low light image enhancement approach using dark channel prior (DCP). Initially, light reflection (retinex) angles are identified and red channel estimation was used to restore light direction attention. Further, DCP is used to identify the background darkness region with light illumination properties. Then, new anthropic light properties were generated by using transmission map estimation and refinement. Further, image light radiance is recovered by using this updated transmission map values, which generates darkness removed image. Finally, denoising operation is performed to get the best visual quality output image. The simulations conducted on ExDark dataset shows that the proposed method resulted in superior subjective and objective performance as compared to state of art approaches.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: 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.