Dynamic pattern denoising method using multi-basin system with kernels

Pattern Recognition

Volumn 44, Issue 8, 2011, Pages 1698-1707

  Jung, Kyu Hwan ^a   Kim, Namhyoung ^a   Lee, Jaewook ^a  

^a Pohang University of Science and Technology (POSTECH)   (South Korea)

Author keywords

Dynamical system; Image restoration; Kernel methods; Pattern denoising; Support vector machines

Indexed keywords

DATA SETS; DE-NOISE; DENOISING METHODS; DYNAMIC PATTERNS; IMAGE RESTORATION; KERNEL METHODS; NOISY PATTERNS; NOVEL PATTERNS; PATTERN DENOISING; REAL IMAGES; SUPPORT FUNCTIONS; TOPOLOGICAL PROPERTIES;

DYNAMICAL SYSTEMS; IMAGE RECONSTRUCTION; LOCOMOTIVES; NOISE POLLUTION CONTROL; RAILROAD CARS; RESTORATION; SUPPORT VECTOR MACHINES; TOPOLOGY;

NORMAL DISTRIBUTION;

EID: 79953062914     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2011.02.004     Document Type: Article

References (28)

1. D.M.J. Tax, and R.P.W. Duin Support vector domain description Pattern Recognition Letters 20 1999 1191 1199 (Pubitemid 32261897)
2. B. Schölkopf, J.C. Platt, J. Shawe-Taylor, A.J. Smola, and R.C. Williamson Estimating the support of a high-dimensional distribution Neural Computation 13 2001 1443 1471 (Pubitemid 33595028)
3. C. Lai, D.M.J. Tax, R.P.W. Duin, E. Pekalska, P. Paclik, On combining one-class classifiers for image database retrieval, in: Lecture Notes in Computer Science, vol. 2364, 2002, pp. 212221.
4. T. Onoda, H. Murata, and S. Yamada Non-relevance feedback document retrieval based on one-class SVM and SVDD Proceeding of 2006 IEEE World Congress on Computational Intelligence 2006 2191 2198
5. J. Yang, V. Estivill-Castro, and S.K. Chalup Support vector clustering through proximity graph modelling Proceedings of the Ninth International Conference on Neural Information Processing (ICONIP'02) 2002 898 903
6. A. Ben-Hur, D. Horn, H.T. Siegelmann, and V. Vapnik Support vector clustering Journal of Machine Learning Research 2 2001 125 137
7. J. Lee, and D. Lee An improved cluster labeling method for support vector clustering IEEE Transactions on Pattern Analysis and Machine Intelligence 27 2005 461 464 (Pubitemid 40377337)
8. J. Lee, and D. Lee Dynamic characterization of cluster structures for robust and inductive support vector clustering IEEE Transactions on Pattern Analysis and Machine Intelligence 28 2006 1869 1874 (Pubitemid 46405432)
9. K.H. Jung, D. Lee, and J. Lee Fast support-based clustering method for large-scale problems Pattern Recognition 43 2010 1975 1983
10. D. Lee, and J. Lee Domain described support vector classifier for multi-class classification problems Pattern Recognition 40 2007 41 51 (Pubitemid 44486292)
11. D. Lee, and J. Lee Equilibrium-based support vector machine for semi-supervised classification IEEE Transactions on Neural Networks 18 2 2007 578 583 (Pubitemid 46522577)
12. D. Lee, K.H. Jung, and J. Lee Constructing sparse kernel machines using attractors IEEE Transactions on Neural Networks 20 4 2009 721 729
13. D. Lee, and J. Lee Dynamic dissimilarity measure for support-based clustering IEEE Transactions on Knowledge and Data Engineering 22 6 2010 900 905
14. H.-C. Kim, and J. Lee Clustering based on gaussian processes Neural Computation 19 11 2007 3088 3107
15. D. Comaniciu, and P. Meer Mean shift: a robust approach toward feature space analysis IEEE Transactions on Pattern Analysis and Machine Intelligence 24 2002 603 619 (Pubitemid 34550429)
16. F. Camastra, and A. Verri A novel kernel method for clustering IEEE Transactions on Pattern Analysis and Machine Intelligence 27 3 2005 461 464
17. C. Cortes, and V. Vapnik Support-vector networks Machine Learning 20 3 1995 273 297
18. J.J. Hull A database for handwritten text recognition IEEE Transactions on Pattern Analysis and Machine Intelligence 16 1994 550 554
19. S.A. Nene, S.K. Nayar, H. Murase, Columbia Object Image Library (COIL-20), Technical Report CUCS-005-96, 1996.
20. J. Lee, and H.D. Chiang Theory of stability regions of a class of non-hyperbolic dynamical systems and its applications to constraint satisfaction problems IEEE Transactions on Circuits and Systems - Part I: Fundamental Theory and Applications 49 2 2002 196 209 (Pubitemid 34291471)
21. M.C. Motwani, M.C. Gadiya, R.C. Motwani, Survey of image denoising techniques, in: Proceedings of GSPx, Santa Clara, CA, 2004.
22. A. Buades, B. Coll, and J.M. Morel On image denoising methods SIAM Multiscale Modeling and Simulation 4 2005 490 530
23. J. Park, D. Kang, J. Kim, J.T. Kwok, and I.W. Tsang SVDD-based pattern denoising Neural Computation 19 7 2007 1919 1938
24. S. Mika, B. Schölkopf, A. Smola, K.R. Müller, M. Scholz, and G. Rätsch Kernel PCA and de-noising in feature spaces Advances in Neural Information Processing Systems 11 1999 536 542
25. J.T. Kwok, and I.W. Tsang The pre-image problem in kernel methods IEEE Transactions on Neural Networks 15 2004 1517 1525
26. D.L. Donoho De-noising by soft-thresholding IEEE Transactions on Information Theory 41 3 1995 613 627
27. F. Camastra, M. Spinetti, and A. Vinciarelli Offline cursive character challenge: a new benchmark for machine learning and pattern recognition algorithms Proceedings of 18th International Conference on Pattern Recognition (ICPR06) 2006 913 916 (Pubitemid 46532348)
28. F. Camastra A SVM-based cursive character recognizer Pattern Recognition 40 12 2007 3721 3727 (Pubitemid 47223273)