A Convex Variational Model for Learning Convolutional Image Atoms from Incomplete Data [0.03%]
基于不完整数据学习卷积图像原子的凸变分模型
A Chambolle,M Holler,T Pock
A Chambolle
A variational model for learning convolutional image atoms from corrupted and/or incomplete data is introduced and analyzed both in function space and numerically. Building on lifting and relaxation strategies, the proposed approach is conv...
Variational Networks: An Optimal Control Approach to Early Stopping Variational Methods for Image Restoration [0.03%]
变分网络：用于早期停止图像恢复变分方法的最优控制方法
Alexander Effland,Erich Kobler,Karl Kunisch et al.
Alexander Effland et al.
We investigate a well-known phenomenon of variational approaches in image processing, where typically the best image quality is achieved when the gradient flow process is stopped before converging to a stationary point. This paradox origina...
Tracking of Lines in Spherical Images via Sub-Riemannian Geodesics in [Formula: see text] [0.03%]
球形图像中的线跟踪via[subformula]中的子黎曼测地线
A Mashtakov,R Duits,Yu Sachkov et al.
A Mashtakov et al.
In order to detect salient lines in spherical images, we consider the problem of minimizing the functional ∫ 0 l C ( γ ( s ) ) ξ 2 + k g 2 ( s ) d s for a curve γ on a sphere with fixed boundary points and directi...
Tuomo Valkonen,Thomas Pock
Tuomo Valkonen
We propose several variants of the primal-dual method due to Chambolle and Pock. Without requiring full strong convexity of the objective functions, our methods are accelerated on subspaces with strong convexity. This yields mixed rates, O ...
Michael Roberts,Jack Spencer
Michael Roberts
Selective segmentation involves incorporating user input to partition an image into foreground and background, by discriminating between objects of a similar type. Typically, such methods involve introducing additional constraints to generi...
Regularization with Metric Double Integrals of Functions with Values in a Set of Vectors [0.03%]
具有向量集值的函数的度量双重积分正则化
René Ciak,Melanie Melching,Otmar Scherzer
René Ciak
We present an approach for variational regularization of inverse and imaging problems for recovering functions with values in a set of vectors. We introduce regularization functionals, which are derivative-free double integrals of such func...
Regularization with Metric Double Integrals of Functions with Values in a Set of Vectors [0.03%]
具有向量集值的函数的度量双重积分正则化
René Ciak,Melanie Melching,Otmar Scherzer
René Ciak
We present an approach for variational regularization of inverse and imaging problems for recovering functions with values in a set of vectors. We introduce regularization functionals, which are derivative-free double integrals of such func...
Optimal Paths for Variants of the 2D and 3D Reeds-Shepp Car with Applications in Image Analysis [0.03%]
二维和三维刘易斯汽车变体的最优路径及在图像分析中的应用
R Duits,S P L Meesters,J-M Mirebeau et al.
R Duits et al.
We present a PDE-based approach for finding optimal paths for the Reeds-Shepp car. In our model we minimize a (data-driven) functional involving both curvature and length penalization, with several generalizations. Our approach encompasses ...
Nilpotent Approximations of Sub-Riemannian Distances for Fast Perceptual Grouping of Blood Vessels in 2D and 3D [0.03%]
二维和三维快速感知血管分组的子黎曼距离的幂零逼近法
Erik J Bekkers,Da Chen,Jorg M Portegies
Erik J Bekkers
We propose an efficient approach for the grouping of local orientations (points on vessels) via nilpotent approximations of sub-Riemannian distances in the 2D and 3D roto-translation groups SE(2) and SE(3). In our distance approximations we...
M H J Janssen,A J E M Janssen,E J Bekkers et al.
M H J Janssen et al.
The enhancement and detection of elongated structures in noisy image data are relevant for many biomedical imaging applications. To handle complex crossing structures in 2D images, 2D orientation scores U : R 2 × S 1 → C were in...