A Second Order Nonsmooth Variational Model for Restoring Manifold-Valued Images

A Second Order Nonsmooth Variational Model for Restoring Manifold-Valued Images
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恢复流形值图像的二阶非光滑变分模型

DOI:
10.1137/15m101988x
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发表时间:
2016
期刊:
SIAM J. Sci. Comput.
影响因子:
--
通讯作者:
A. Weinmann
A. Weinmann
中科院分区:
--
文献类型:
--
作者:
Bačák;R. Bergmann;G. Steidl;A. Weinmann

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我们引入了一个新的非光滑变分模型的恢复流形值的数据,其中包括二阶差分的正则项。虽然这样的模型被成功地应用于实值图像,我们介绍了二阶差分和相应的变分模型的流形数据,到目前为止只存在于循环数据。该方法需要从数值分析,凸优化和微分几何的技术相结合。首先,我们建立了一个合适的定义绝对二阶差分的信号和图像的值在一个流形。采用这一定义,我们介绍了一个变分去噪模型的基础上的第一和第二阶差分的流形设置。为了最小化相应的功能,我们开发了一个算法,使用不精确的循环邻近点算法。我们提出了一个有效的策略,计算相应的邻近映射在对称空间中利用雅可比场的机器。对于球面和对称正定矩阵流形,我们证明了我们的算法在实践中的性能。我们证明了Hadamard空间中的循环邻近点算法的精确和不精确变体的收敛性。这些结果本身就令人感兴趣,例如,对称正定矩阵的流形。
We introduce a new nonsmooth variational model for the restoration of manifold-valued data which includes second order differences in the regularization term. While such models were successfully applied for real-valued images, we introduce the second order difference and the corresponding variational models for manifold data, which up to now only existed for cyclic data. The approach requires a combination of techniques from numerical analysis, convex optimization, and differential geometry. First, we establish a suitable definition of absolute second order differences for signals and images with values in a manifold. Employing this definition, we introduce a variational denoising model based on first and second order differences in the manifold setup. In order to minimize the corresponding functional, we develop an algorithm using an inexact cyclic proximal point algorithm. We propose an efficient strategy for the computation of the corresponding proximal mappings in symmetric spaces utilizing the machinery of Jacobi fields. For the-sphere and the manifold of symmetric positive definite matrices, we demonstrate the performance of our algorithm in practice. We prove the convergence of the proposed exact and inexact variant of the cyclic proximal point algorithm in Hadamard spaces. These results which are of interest on its own include, e.g., the manifold of symmetric positive definite matrices.
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