Adaptive Weighted least Squares SVM Based snowing Model for Image Denoising
暂无分享,去创建一个
Emile A. Hendriks | Xiaojun Wang | Sheng Zheng | Changcai Yang | Sheng Zheng | E. Hendriks | Changcai Yang | Xiaojun Wang
[1] Li Xia,et al. Image Denoising Based on the Dyadic Wavelet Transform and Improved Threshold , 2009, Int. J. Wavelets Multiresolution Inf. Process..
[2] Dalong Li,et al. Support vector regression based image denoising , 2009, Image Vis. Comput..
[3] Lixin Shen,et al. Framelet Algorithms for De-Blurring Images Corrupted by Impulse Plus Gaussian Noise , 2011, IEEE Transactions on Image Processing.
[4] Qionghai Dai,et al. Image and Video Denoising Using Adaptive Dual-Tree Discrete Wavelet Packets , 2009, IEEE Transactions on Circuits and Systems for Video Technology.
[5] Martin J. Wainwright,et al. Image denoising using scale mixtures of Gaussians in the wavelet domain , 2003, IEEE Trans. Image Process..
[6] Seongjai Kim,et al. PDE-based image restoration: a hybrid model and color image denoising , 2006, IEEE Transactions on Image Processing.
[7] David Zhang,et al. Two-stage image denoising by principal component analysis with local pixel grouping , 2010, Pattern Recognit..
[8] J. Mercer. Functions of Positive and Negative Type, and their Connection with the Theory of Integral Equations , 1909 .
[9] Zhaowei Shang,et al. Image Denoising Based on Gaussian and Non-Gaussian Assumption , 2012, Int. J. Wavelets Multiresolution Inf. Process..
[10] Johan A. K. Suykens,et al. Least Squares Support Vector Machines , 2002 .
[11] Joseph Y. Lo,et al. Efficient Fourier-Wavelet Super-Resolution , 2010, IEEE Transactions on Image Processing.
[12] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[13] R. Lai,et al. Accelerating non-local means algorithm with random projection , 2011 .
[14] Jian-Huang Lai,et al. Learning an Adaptive Dictionary Using a Projected Gradient Method and its Application on Image de-noising , 2012, Int. J. Wavelets Multiresolution Inf. Process..
[15] M. Elad,et al. $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation , 2006, IEEE Transactions on Signal Processing.
[16] Johan A. K. Suykens,et al. Weighted least squares support vector machines: robustness and sparse approximation , 2002, Neurocomputing.
[17] Bernhard Schölkopf,et al. Iterative kernel principal component analysis for image modeling , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[18] Peyman Milanfar,et al. Kernel Regression for Image Processing and Reconstruction , 2007, IEEE Transactions on Image Processing.
[19] Levent Sendur,et al. Bivariate shrinkage functions for wavelet-based denoising exploiting interscale dependency , 2002, IEEE Trans. Signal Process..
[20] Raymond H. Chan,et al. An Efficient Two-Phase ${\rm L}^{1}$-TV Method for Restoring Blurred Images with Impulse Noise , 2010, IEEE Transactions on Image Processing.
[21] Guangming Shi,et al. Robust adaptive directional lifting wavelet transform for image denoising , 2011 .
[22] Samuel Morillas,et al. Fuzzy Peer Groups for Reducing Mixed Gaussian-Impulse Noise From Color Images , 2009, IEEE Transactions on Image Processing.
[23] Peter J. Rousseeuw,et al. Robust Regression and Outlier Detection , 2005, Wiley Series in Probability and Statistics.
[24] Xavier Bresson,et al. Nonlocal Mumford-Shah Regularizers for Color Image Restoration , 2011, IEEE Transactions on Image Processing.
[25] Alessandro Foi,et al. Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering , 2007, IEEE Transactions on Image Processing.
[26] Etienne E. Kerre,et al. Fuzzy Random Impulse Noise Removal From Color Image Sequences , 2011, IEEE Transactions on Image Processing.
[27] Xinghuo Yu,et al. Geometric Features-Based Filtering for Suppression of Impulse Noise in Color Images , 2009, IEEE Transactions on Image Processing.
[28] Venkateswara Rao,et al. Adaptive Kernel-Based Image Denoising Employing Semi-Parametric Regularization , 2012 .
[29] Vladimir Cherkassky,et al. The Nature Of Statistical Learning Theory , 1997, IEEE Trans. Neural Networks.
[30] I. Selesnick,et al. Bivariate shrinkage with local variance estimation , 2002, IEEE Signal Processing Letters.
[31] Paul Fearing,et al. Computer modelling of fallen snow , 2000, SIGGRAPH.