Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
Imaging vector fields using line integral convolution
SIGGRAPH '93 Proceedings of the 20th annual conference on Computer graphics and interactive techniques
Numerical Methods for p-Harmonic Flows and Applications to Image Processing
SIAM Journal on Numerical Analysis
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Vector-Valued Image Regularization with PDEs: A Common Framework for Different Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Non-Local Algorithm for Image Denoising
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Fast Anisotropic Smoothing of Multi-Valued Images using Curvature-Preserving PDE's
International Journal of Computer Vision
Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations (Applied Mathematical Sciences)
Convex Hodge Decomposition and Regularization of Image Flows
Journal of Mathematical Imaging and Vision
A Curvilinear Search Method for $p$-Harmonic Flows on Spheres
SIAM Journal on Imaging Sciences
A TV-stokes denoising algorithm
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
Diffusion-Like reconstruction schemes from linear data models
DAGM'06 Proceedings of the 28th conference on Pattern Recognition
Total variation minimization and a class of binary MRF models
EMMCVPR'05 Proceedings of the 5th international conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
A theory of multiple orientation estimation
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Noise removal using smoothed normals and surface fitting
IEEE Transactions on Image Processing
Analysis of Superimposed Oriented Patterns
IEEE Transactions on Image Processing
A Short- Time Beltrami Kernel for Smoothing Images and Manifolds
IEEE Transactions on Image Processing
A unifying approach to isotropic and anisotropic total variation denoising models
Journal of Computational and Applied Mathematics
Orientation-Matching Minimization for Image Denoising and Inpainting
International Journal of Computer Vision
Denoising time-of-flight data with adaptive total variation
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
Variational image denoising with adaptive constraint sets
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
A class of quasi-variational inequalities for adaptive image denoising and decomposition
Computational Optimization and Applications
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To improve the quality of image restoration methods directional information has recently been involved in the restoration process. In this paper, we propose a two step procedure for denoising images that is particularly suited to recover sharp vertices and X junctions in the presence of heavy noise. In the first step, we estimate the (smoothed) orientations of the image structures, where we find the double orientations at vertices and X junctions using a model of Aach et al. Based on shape preservation considerations this directional information is then applied to establish an energy functional which is minimized in the second step. We discuss the behavior of our new method in comparison with single direction approaches appearing, e.g., when using the classical structure tensor of Förstner and Gülch and demonstrate the very good performance of our method by numerical examples.