On the Direction Guidance in Structure Tensor Total Variation Based Denoising

Abstract

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.