Total Directional Variation for Video Denoising

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Abstract

In this paper we propose a variational approach for video denoising, based on a total directional variation (TDV) regulariser proposed in [20, 21] for image denoising and interpolation. In the TDV regulariser, the underlying image structure is encoded by means of weighted derivatives so as to enhance the anisotropic structures in images, e.g. stripes or curves with a dominant local directionality. For the extension of TDV to video denoising, the space-time structure is captured by the volumetric structure tensor guiding the smoothing process. We discuss this and present our whole video denoising workflow. The numerical results are compared with some state-of-the-art video denoising methods.

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Parisotto, S., & Schönlieb, C. B. (2019). Total Directional Variation for Video Denoising. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11603 LNCS, pp. 522–534). Springer Verlag. https://doi.org/10.1007/978-3-030-22368-7_41

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