Title: Video Denoising via Directional Fractional Order Total Variation

 

Abstract: Video denoising is one of the fundamental tasks in computer vision and medical imaging. In this talk, we propose a novel denoising method for spatiotemporal video data based on the Directional Fractional Order Total Variation (DFTV) regularization and Huber loss. We will begin with the basics of image denoising, introduce our DFTV regularized video denoising model, and derive an efficient numerical algorithm. Various numerical results will be presented to show the robustness and performance of our method.