Adaptive Two-Pass Median Filter Based on Support Vector Machines for Image Restoration
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[1] Kaoru Arakawa,et al. Median filter based on fuzzy rules and its application to image restoration , 1996, Fuzzy Sets Syst..
[2] Pao-Ta Yu,et al. An Optimal Design of Fuzzy (m, n) Rank Order Filtering with Hard Decision Neural Learning , 1995, Proceedings of ISCAS'95 - International Symposium on Circuits and Systems.
[3] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[4] F. Russo,et al. A fuzzy filter for images corrupted by impulse noise , 1996, IEEE Signal Processing Letters.
[5] Kai-Kuang Ma,et al. Tri-state median filter for image denoising , 1999, IEEE Trans. Image Process..
[6] Hideaki Sakai,et al. Convergence behavior of the LMS algorithm in subband adaptive filtering , 2001, Signal Process..
[7] Chih-Jen Lin,et al. A formal analysis of stopping criteria of decomposition methods for support vector machines , 2002, IEEE Trans. Neural Networks.
[8] Pao-Ta Yu,et al. Centroid neural network adaptive resonance theory for vector quantization , 2003, Signal Process..
[9] Pao-Ta Yu,et al. Partition fuzzy median filter based on fuzzy rules for image restoration , 2004, Fuzzy Sets Syst..
[10] F. Russo,et al. Fuzzy systems in instrumentation: fuzzy signal processing , 1995, Proceedings of 1995 IEEE Instrumentation and Measurement Technology Conference - IMTC '95.
[11] Kwanghoon Sohn,et al. Detection-estimation based approach for impulsive noise removal , 1998 .
[12] Takao Hinamoto,et al. A new adaptive center weighted median filter using counter propagation networks , 2000, J. Frankl. Inst..
[13] Giovanni Ramponi,et al. A noise smoother using cascaded FIRE filters , 1995, Proceedings of 1995 IEEE International Conference on Fuzzy Systems..
[14] M. S. Bazaraa,et al. Nonlinear Programming , 1979 .
[15] Marti A. Hearst. Trends & Controversies: Support Vector Machines , 1998, IEEE Intell. Syst..
[16] Fabrizio Russo. Evolutionary neural fuzzy systems for noise cancellation in image data , 1999, IEEE Trans. Instrum. Meas..
[17] Chih-Jen Lin,et al. On the convergence of the decomposition method for support vector machines , 2001, IEEE Trans. Neural Networks.
[18] Gunnar Rätsch,et al. An introduction to kernel-based learning algorithms , 2001, IEEE Trans. Neural Networks.
[19] Simon Haykin,et al. Neural Networks: A Comprehensive Foundation , 1998 .
[20] Fabrizio Russo,et al. FIRE operators for image processing , 1999, Fuzzy Sets Syst..
[21] Miki Haseyama,et al. An accurate noise detector for image restoration , 2002, Proceedings. International Conference on Image Processing.
[22] Zhou Wang,et al. Progressive switching median filter for the removal of impulse noise from highly corrupted images , 1999 .
[23] H. Wu,et al. Adaptive impulse detection using center-weighted median filters , 2001, IEEE Signal Processing Letters.
[24] Azeddine Beghdadi,et al. A noise-filtering method using a local information measure , 1997, IEEE Trans. Image Process..
[25] Chih-Jen Lin,et al. The analysis of decomposition methods for support vector machines , 2000, IEEE Trans. Neural Networks Learn. Syst..
[26] Tao Chen,et al. Recursive implementation of constrained LMS L-filters for image restoration , 2001, Signal Process..
[27] Yrjö Neuvo,et al. Detail-preserving median based filters in image processing , 1994, Pattern Recognit. Lett..
[28] Pao-Ta Yu,et al. Adaptive fuzzy hybrid multichannel filters for removal of impulsive noise from color images , 1999, Signal Process..
[29] Pao-Ta Yu,et al. Genetic-based fuzzy hybrid multichannel filters for color image restoration , 2000, Fuzzy Sets Syst..
[30] Chih-Jen Lin,et al. A comparison of methods for multiclass support vector machines , 2002, IEEE Trans. Neural Networks.
[31] Tao Chen,et al. Application of partition-based median type filters for suppressing noise in images , 2001, IEEE Trans. Image Process..
[32] Chih-Jen Lin,et al. Training v-Support Vector Regression: Theory and Algorithms , 2002, Neural Computation.
[33] Nello Cristianini,et al. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .
[34] Eduardo Abreu,et al. A signal-dependent rank ordered mean (SD-ROM) filter-a new approach for removal of impulses from highly corrupted images , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.
[35] Sung-Jea Ko,et al. Center weighted median filters and their applications to image enhancement , 1991 .
[36] Chih-Jen Lin,et al. Asymptotic convergence of an SMO algorithm without any assumptions , 2002, IEEE Trans. Neural Networks.
[37] Moncef Gabbouj,et al. Weighted median filters: a tutorial , 1996 .
[38] Tao Chen,et al. Impulse noise removal by multi-state median filtering , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).
[39] J. Astola,et al. Fundamentals of Nonlinear Digital Filtering , 1997 .
[40] Michael L. Lightstone,et al. A new efficient approach for the removal of impulse noise from highly corrupted images , 1996, IEEE Trans. Image Process..
[41] Ronald W. Schafer,et al. Decision-based median filter using local signal statistics , 1994, Other Conferences.
[42] Chih-Jen Lin,et al. A Simple Decomposition Method for Support Vector Machines , 2002, Machine Learning.
[43] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[44] Vladimir Vapnik,et al. Statistical learning theory , 1998 .