2019-09-22
On the direction guidance in structure tensor total variation based denoising
Publication
Publication
Presented at the
Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2019) (July 2019), Madrid, Spain
This paper introduces a new analysis-based regularizer, which incorporates the neighborhood-awareness of the structure tensor total variation (STV) and the tunability of the directional total variation (DTV), in favor of a pre-selected direction with a pre-selected dose of penalization. In order to show the utility of the proposed regularizer, we consider the problem of denoising uni-directional images. Since the regularizer is convex, we develop a simple optimization algorithm by realizing its proximal map. The quantitative and the visual experiments demonstrate the superiority of our regularizer over DTV (only for scalar-valued images) and STV.
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doi.org/10.1007/978-3-030-31332-6_8 | |
Lecture Notes in Computer Science | |
Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2019) | |
Demircan Türeyen, E., & Kamaşak, M. E. (2019). On the direction guidance in structure tensor total variation based denoising. In Proceedings of the Iberian Conference on Pattern Recognition and Image Analysis. doi:10.1007/978-3-030-31332-6_8 |