Abstract
This paper presents a novel denoising scheme for video sequences corrupted by mixed Gaussian-impulse noise. From a global viewpoint, such a video sequence contains three parts: temporal-spatially correlated video content, uncorrelated dense Gaussian noise, and uncorrelated sparse impulse noise. This fact motivates us to formulate the mixed Gaussian-impulse noise removal task as a temporal-spatial decomposition problem, which amounts to a convex program. A two-stage algorithm is developed to solve this problem efficiently. Effectiveness of the proposed algorithm on mixed Gaussian-impulse noise removal is validated through experiments. The results are satisfactory in both visual quality and PSNR values, while very few prior knowledge of noise statistic is required compared to most 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.
