The Total Variation Regularized L1 Model for Multiscale Decomposition
The Total Variation Regularized L1 Model for Multiscale Decomposition
复制标题
DOI：
10.1137/060663027
复制
发表时间：
2007-04
期刊：
影响因子：
--
通讯作者：
W. Yin;D. Goldfarb;S. Osher
中科院分区：
文献类型：
--
作者：
W. Yin;D. Goldfarb;S. Osher
摘要：研究了带L1保真度项的全变分正则化模型（TV-L1），用于将图像分解为不同尺度的特征。我们首先证明了由该模型产生的图像可以由一系列解耦几何子问题的极小值形成。利用这一结果，我们表明TV-L1模型能够根据尺度分离图像特征，其中尺度由g值解析定义。证明了TV-L1模型的几何不变性和形态不变性，并讨论了它们的应用。
Abstract : This paper studies the total variation regularization model with an L1 fidelity term (TV-L1) for decomposing an image into features of different scales. We first show that the images produced by this model can be formed from the minimizers of a sequence of decoupled geometry sub-problems. Using this result we show that the TV-L1 model is able to separate image features according to their scales, where the scale is analytically defined by the G-value. A number of other properties including the geometric and morphological invariance of the TV-L1 model are also proved and their applications discussed.