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
Prior Learning and Gibbs Reaction-Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast texture synthesis using tree-structured vector quantization
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
An Algorithm for Finding Best Matches in Logarithmic Expected Time
ACM Transactions on Mathematical Software (TOMS)
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
Diffusions and Confusions in Signal and Image Processing
Journal of Mathematical Imaging and Vision
Atomic Decomposition by Basis Pursuit
SIAM Review
Example-Based Super-Resolution
IEEE Computer Graphics and Applications
Limits on Super-Resolution and How to Break Them
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture Synthesis by Non-Parametric Sampling
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Fields of Experts: A Framework for Learning Image Priors
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Method of optimal directions for frame design
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 05
-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
IEEE Transactions on Signal Processing
Universal discrete denoising: known channel
IEEE Transactions on Information Theory
Image compression via joint statistical characterization in the wavelet domain
IEEE Transactions on Image Processing
A VQ-based blind image restoration algorithm
IEEE Transactions on Image Processing
Region filling and object removal by exemplar-based image inpainting
IEEE Transactions on Image Processing
Image Restoration Using Piecewise Iterative Curve Fitting and Texture Synthesis
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
A plurality of sparse representations is better than the sparsest one alone
IEEE Transactions on Information Theory
Image upscaling using global multimodal priors
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
A groupwise super-resolution approach: application to brain MRI
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Journal of Mathematical Imaging and Vision
Sparsity-based super-resolution for offline handwriting recognition
Proceedings of the 2011 Joint Workshop on Multilingual OCR and Analytics for Noisy Unstructured Text Data
Vehicle license plate super-resolution using soft learning prior
Multimedia Tools and Applications
Reconstruction of low-resolution images using adaptive bimodal priors
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Solving the inverse problem of image zooming using "self-examples"
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Super-resolution of single text image by sparse representation
Proceeding of the workshop on Document Analysis and Recognition
Single image super resolution reconstruction in perturbed exemplar sub-space
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
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Regularization plays a vital role in inverse problems, and especially in ill-posed ones. Along with classical regularization techniques based on smoothness, entropy, and sparsity, an emerging powerful regularization is one that leans on image examples. In this paper, we propose an efficient scheme for using image examples as driving a powerful regularization, applied to the image scale-up (super-resolution) problem. In this work, we target specifically scanned documents containing written text, graphics, and equations. Our algorithm starts by assigning per each location in the degraded image several candidate high-quality patches. Those are found as the nearest-neighbors (NN) in an image-database that contains pairs of corresponding low- and high-quality image patches. The found examples are used for the definition of an image prior expression, merged into a global MAP penalty function. We use this penalty function both for rejecting some of the irrelevant outlier examples, and then for reconstructing the desired image. We demonstrate our algorithm on several scanned documents with promising results.