Proceedings of the 27th annual conference on Computer graphics and interactive techniques
A two-dimensional interpolation function for irregularly-spaced data
ACM '68 Proceedings of the 1968 23rd ACM national conference
Texture Synthesis by Non-Parametric Sampling
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Learning How to Inpaint from Global Image Statistics
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Image completion with structure propagation
ACM SIGGRAPH 2005 Papers
Unsupervised, Information-Theoretic, Adaptive Image Filtering for Image Restoration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Graph regularization for color image processing
Computer Vision and Image Understanding
Non-local Regularization of Inverse Problems
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
A Variational Framework for Non-local Image Inpainting
EMMCVPR '09 Proceedings of the 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
Generalizing the Nonlocal-means to super-resolution reconstruction
IEEE Transactions on Image Processing
Self-similarity driven color demosaicking
IEEE Transactions on Image Processing
-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
IEEE Transactions on Signal Processing
Simultaneous structure and texture image inpainting
IEEE Transactions on Image Processing
Region filling and object removal by exemplar-based image inpainting
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Optimal Spatial Adaptation for Patch-Based Image Denoising
IEEE Transactions on Image Processing
Efficient Nonlocal Means for Denoising of Textural Patterns
IEEE Transactions on Image Processing
A Variational Framework for Exemplar-Based Image Inpainting
International Journal of Computer Vision
Contour Stencils: Total Variation along Curves for Adaptive Image Interpolation
SIAM Journal on Imaging Sciences
Geometrically Guided Exemplar-Based Inpainting
SIAM Journal on Imaging Sciences
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A nonlocal variational formulation for interpolating a sparsely sampled image is introduced in this paper. The proposed variational formulation, originally motivated by image inpainting problems, encourages the transfer of information between similar image patches, following the paradigm of exemplar-based methods. Contrary to the classical inpainting problem, no complete patches are available from the sparse image samples, and the patch similarity criterion has to be redefined as here proposed. Initial experimental results with the proposed framework, at very low sampling densities, are very encouraging. We also explore some departures from the variational setting, showing a remarkable ability to recover textures at low sampling densities.