On the Direction Guidance in Structure Tensor Total Variation Based Denoising - Demircan-Tureyen, Ezgi (My University, 2019)
This paper introduces a new analysis-based regularizer, which incor porates 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 opti mization algorithm by realizing its proximal map. The quantitative and visual experiments demonstrate the superiority of our regularizer over DTV (only for scalar-valued images) and STV.
Keywords: Image Denoising; Total Variation; Structure Tensor; Directional Total Variation; Convex Optimization; Inverse Problems