Total generalized variation for graph signals
Total generalized variation for graph signals
复制标题
DOI：
10.1109/icassp.2015.7179014
复制
发表时间：
2015-04
期刊：
影响因子：
--
通讯作者：
Shunsuke Ono;I. Yamada;I. Kumazawa
中科院分区：
文献类型：
--
作者：
Shunsuke Ono;I. Yamada;I. Kumazawa
本文提出了一种二阶离散全广义变分（TGV），我们称之为图TGV（G-TGV）。原始的TGV是作为众所周知的全变差（TV）的自然高阶扩展而引入的，并且是分段平滑信号的有效先验。类似地，所提出的G-TGV是图形信号TV（G-TV）的扩展，并且继承了TGV的能力，例如避免阶梯效应。因此，G-TGV有望成为图形信号处理的基本构建模块。我们提供了它的应用程序，分段平滑图形信号修复和三维网格平滑说明性的实验结果。
This paper proposes a second-order discrete total generalized variation (TGV) for arbitrary graph signals, which we call the graph TGV (G-TGV). The original TGV was introduced as a natural higher-order extension of the well-known total variation (TV) and is an effective prior for piecewise smooth signals. Similarly, the proposed G-TGV is an extension of the TV for graph signals (G-TV) and inherits the capability of the TGV, such as avoiding staircasing effect. Thus the G-TGV is expected to be a fundamental building block for graph signal processing. We provide its applications to piecewise-smooth graph signal inpainting and 3D mesh smoothing with illustrative experimental results.