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