Image Super-Resolution Via Sparse Representation

Keywords

Sparse approximation, Artificial intelligence, Pattern recognition (psychology), Computer science, Image (mathematics)

References

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• For most large underdetermined systems of linear equations the minimal 𝓁1‐norm solution is also the sparsest solutionDavid L. Donoho — 2006
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• Learning Sparse Overcomplete Codes for ImagesJoseph F. Murray, Kenneth Kreutz-Delgado — 2006
• Learning Multiscale Sparse Representations for Image and Video RestorationJulien Mairal, Guillermo Sapiro, Michael Elad — 2008
• Example-Based Super-ResolutionWilliam T. Freeman, Thouis R. Jones, Egon Pasztor — 2002
• Limits on super-resolution and how to break themSimon Baker, Takeo Kanade — 2000
• Patch based blind image super resolutionQiang Wang, Xiaoou Tang, Heung‐Yeung Shum — 2005
• Sparse coding with an overcomplete basis set: a strategy employed by V1?Bruno A. Olshausen, David J. Field — 1997
• Compressed Sensing and Redundant DictionariesHolger Rauhut, Karin Schnass, Pierre Vandergheynst — 2007
• Joint MAP registration and high-resolution image estimation using a sequence of undersampled imagesRussell C. Hardie, Kenneth J. Barnard, Ernest E. Armstrong — 1997
• For most large underdetermined systems of equations, the minimal 𝓁1‐norm near‐solution approximates the sparsest near‐solutionDavid L. Donoho — 2006
• Image hallucination with primal sketch priorsJian Sun, Nanning Zheng, Hai Tao — 2003
• Super-resolution through neighbor embeddingHong Chang, Dit‐Yan Yeung, Yimin Xiong — 2004

Cited by

• A Compressed Sensing Approach for MR Tissue Contrast SynthesisSnehashis Roy, Aaron Carass, Jerry L. Prince — 2011
• Face Super-Resolution via Multilayer Locality-Constrained Iterative Neighbor Embedding and Intermediate Dictionary LearningJunjun Jiang, Ruimin Hu, Zhongyuan Wang — 2014
• Vector Sparse Representation of Color Image Using Quaternion Matrix AnalysisDamien Kingsbury, Michael Leach — 2015
• Machine Learning Based Single-Frame Super-Resolution Processing for Lensless Blood Cell Counting泰代 野村 — 2016
• Single image super-resolution via an iterative reproducing kernel Hilbert space methodAlfonso Villahermosa — 2015
• A NOVEL IMAGE-SPECIFIC TRANSFER APPROACH FOR PROSTATE SEGMENTATION IN MR IMAGESAlberto Moreno Doña — 2018
• Enhance Visual Recognition Under Adverse Conditions via Deep NetworksDing Liu, Bowen Cheng, Zhangyang Wang — 2017
• Sparse coding for machine learning, image processing and computer visionJulien Mairal — 2010
• Learning-based super-resolution with applications to intensity and depth imagesHaoheng Zheng — 2014
• Kinect based system applied to breast cancer conservative treatmentMarco Alexandre Dias Silva — 2012
• Supervised algorithm selection for flow and other computer vision problemsOisin Mac Aodha — 2014
• Compressive Point Cloud Super ResolutionCody S. Smith — 2012
• Single Image Super Resolution via Manifold ApproximationChinh Dang, Hayder Radha — 2014
• Face Recognition at a Distance: a study of super resolutionYuxi Peng — 2011
• Bayesian Dictionary Learning for Single and Coupled Feature SpacesLi He — 2013
• Non-local Means Resolution Enhancement of Lung 4D-CT DataYu Zhang, Guorong Wu, Pew‐Thian Yap — 2012
• Psychologically inspired dimensionality reduction for 2D and 3D Face RecognitionMark Hansen, Gary A. Atkinson, Melvyn Smith — 2011
• Development of Image Super-resolution AlgorithmsMayank Agrawal — 2013
• Structured Sparse Recovery via Convex OptimizationEhsan Elhamifar, René Vidal — 2011
• Hyperspectral Imagery Super-Resolution by Adaptive POCS and Blur MetricShaoxing Hu, Shuyu Zhang, Aiwu Zhang — 2017

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