Single Depth Image Super Resolution and Denoising Using Coupled Dictionary Learning with Local Constraints and Shock Filtering Jun Xie1, Cheng-Chuan Chou2, Rogerio Feris3, Ming-Ting Sun1 1University of Washington, 2Indus

Source URL: www.clairexie.org

Journal of Machine Learning Research xxxx Submitted xx/xx; Published xx/xx Image denoising with multi-layer perceptrons, part 2: training trade-offs and analysis of their mechanisms

Source URL: arxiv.org

Image interpolation and denoising for division of focal plane sensors using Gaussian Processes Elad Gilboa,1 John P. Cunningham,2 Arye Nehorai,1 and Viktor Gruev 3 1 Preston

Source URL: stat.columbia.edu

• Multivariate interpolation
• Image processing
• Interpolation
• Gaussian process
• Bicubic interpolation
• Polarization
• Regression analysis
• Kalman filter
• Normal distribution
• Kriging

Die Fakultät für Informatik der Universität Wien lädt Sie herzlich ein zum CS-Colloquium The SURE-LET Methodology for Image Denoising

Source URL: cs.univie.ac.at

• Signal processing
• Wavelet
• Noise reduction
• Noise
• Total variation denoising

Journal of Machine Learning Research xxxx Submitted xx/xx; Published xx/xx Image denoising with multi-layer perceptrons, part 1: comparison with existing algorithms and with bounds

Source URL: arxiv.org

Patch Group Based Nonlocal Self-Similarity Prior Learning for Image Denoising Jun Xu1 , Lei Zhang1,∗ , Wangmeng Zuo2 , David Zhang1 , and Xiangchu Feng3 1 2

Source URL: www.cv-foundation.org

Possible contributions to the NEAT simulations André Moitinho & Alberto Krone-Martins U. Lisbon Denoising at the image level

Source URL: neat.obs.ujf-grenoble.fr

Image denoising using scale mixtures of gaussians in the wavelet domain - Image Processing, IEEE Transactions on

Source URL: www.cns.nyu.edu

IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 18, NO. 4, APRILPCA-Based Spatially Adaptive Denoising of CFA Images for Single-Sensor Digital Cameras

Source URL: www4.comp.polyu.edu.hk

SPATIALLY ADAPTIVE IMAGE DENOISING UNDER OVERCOMPLETE EXPANSION Xin Li and Michael T. Orchard Department of Electrical Engineering Princeton University Email: lixin, ABSTRACT

Source URL: www.csee.wvu.edu