A new adaptive center weighted median filter for suppressing impulsive noise in images

Information Sciences

Volumn 177, Issue 4, 2007, Pages 1073-1087

  Lin, Tzu Chao ^a  

^a WUFENG INSTITUTE OF TECHNOLOGY   (Taiwan)

Author keywords

Impulsive noise; Least mean square; Median filter; Scalar quantization

Indexed keywords

IMAGE PROCESSING; IMPULSE NOISE; LEAST SQUARES APPROXIMATIONS; NOISE ABATEMENT; OPTIMIZATION; VECTOR QUANTIZATION;

LEAST MEAN SQUARE (LMS); MEDIAN FILTER; NOISE SUPPRESSION; SCALAR QUANTIZATION;

ADAPTIVE FILTERING;

EID: 33751217714     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2006.07.030     Document Type: Article

References (47)

1. E. Abreu, S.K. Mitra, A signal-dependent rank ordered mean (SD-ROM) filter. A new approach for removal of impulses from highly corrupted images, in: Proceedings of IEEE ICASSP-95, Detroit, MI, 1995, pp. 2371-2374.
2. Almansa A., and Lindeberg T. Fingerprint enhancement by shape adaptation of scale-space operators with automatic scale selection. IEEE Transactions on Image Processing 9 (2000) 2027-2042
3. Ando S., Sakamoto E., and Iba H. Evolutionary modeling and inference of gene network. Information Sciences 145 (2002) 237-259
4. Arakawa K. Median filters based on fuzzy rules and its application to image restoration. Fuzzy Sets and Systems 77 (1996) 3-13
5. Arce G.R. A general weighted median filter structure admitting negative weights. IEEE Transactions on Signal Processing 46 (1998) 3195-3205
6. Astola J., and Kuosmanen P. Fundamentals of Nonlinear Digital Filtering (1997), CRC, Boca Raton, FL
7. Boukerrou K., and Kurz L. Suppression of "salt and pepper" noise based on Youden designs. Information Sciences 110 (1998) 217-235
8. Chen T., and Wu H.R. Space variant median filters for the restoration of impulse noise corrupted images. IEEE Transactions on Circuits and Systems-II: Analog and Digital Signal Processing 48 (2001) 784-789
9. Chen T., Ma K.K., and Chen L.H. Tri-state median filter for image denoising. IEEE Transactions on Image Processing 8 (1999) 1834-1838
10. T. Chen, H.R. Wu, Impulse noise removal by multi-state median filtering, in: Proceedings of IEEE International Conference on Acoustics, Speech, Signal Processing, 2000, pp. 2183-2186.
11. Chen T., and Wu H.R. Adaptive impulse detection using center-weighted median filters. IEEE Signal Processing Letters 8 (2001) 1-3
12. Fischer V., Lukac R., and Martin K. Cost-effective video filtering solution for real-time vision systems. EURASIP Journal on Applied Signal Processing 2005 (2005) 2026-2042
13. D.A.F. Florencio, R.W. Schafer, Decision-based median filter using local signal statistics, in: Proceedings of SPIE Symposium, Visual Communication Image Processing, 1994, pp. 268-275.
14. Freeman W.T., and Adelson E.H. The design and use of steerable filters. IEEE Transactions on Pattern Analysis Machine Intelligence 13 (1991) 891-906
15. Garnett R., Huegerich T., Chui C., and He W. A universal noise removal algorithm with an impulse detector. IEEE Transactions on Image Processing 11 (2005) 1747-1754
16. Greenberg S., and Kogan D. Improved structure-adaptive anisotropic filter. Pattern Recognition Letters 27 (2006) 59-65
17. Hardie R.C., and Boncelet C.G. LUM filters: a class of rank-order-based filters for smoothing and sharpening. IEEE Transactions on Signal Processing 41 (1993) 1061-1076
18. Haykin S. Neural Networks a Comprehensive Foundation. second ed. (1999), Prentice-Hall
19. Hruschka E.R., Campello R.J.G.B., and de Castro L.N. Evolving clusters in gene-expression data. Information Sciences 176 (2006) 1898-1927
20. Kalluri S., and Arce G.R. Adaptive weighted myriad filter algorithms for robust signal processing in α-stable noise environments. IEEE Transactions on Signal Processing 46 (1998) 322-334
21. Ko S.J., and Lee Y.H. Center weighted median filters and their applications to image enhancement. IEEE Transactions on Circuits and Systems 38 (1991) 984-993
22. K. Kondo, M. Haseyama, H. Kitajima, An accurate noise detector for image restoration, in: Proceedings of IEEE International Conference on Image Processing, 2002, pp. 321-324.
23. Kotropoulos C., and Pitas I. Adaptive LMS L-filters for noise suppression in images. IEEE Transactions on Image Processing 5 (1996) 1596-1609
24. Kotropoulos C., and Pitas I. Constrained adaptive LMS L-filters. Signal Processing 26 (1992) 335-358
25. Lin T.-C., and Yu P.-T. Partition fuzzy median filter based on fuzzy rules for image restoration. Fuzzy Sets and Systems 147 (2004) 75-97
26. Lin T.-C., and Yu P.-T. Adaptive two-pass median filter based on support vector machine for image restoration. Neural Computation 16 (2004) 333-354
27. Lin T.-C., and Yu P.-T. Impulse noise detection and removal using multiple thresholds for image restoration. Journal of Information Science and Engineering 22 (2006) 189-198
28. Lin T.-C., and Yu P.-T. Thresholding noise-free ordered mean filter based on Dempster-Shafer theory for image restoration. IEEE Transactions on Circuits and Systems-I: Regular Papers 53 (2006) 1057-1064
29. Lukac R. Binary LUM Smoothing. IEEE Signal Processing Letters 19 (2002) 400-403
30. Lukac R., Plataniotis K.N., Smolka B., and Venetsanopoulos A.N. Generalized selection weighted vector filters. EURASIP Journal on Applied Signal Processing 2004 (2004) 1870-1885
31. Lukac R. Performance boundaries of optimal weighted median filters. International Journal of Image and Graphics 4 (2004) 157-182
32. Lukac R., and Marchevsky S. Boolean expression of LUM smoothers. IEEE Signal Processing Letters 8 (2001) 292-294
33. Lukac R., and Marchevsky S. LUM smoother with smooth control for noisy image sequences. EURASIP Journal on Applied Signal Processing 2001 (2001) 110-120
34. Lukac R., Smolka B., Martin K., Plataniotis K.N., and Venetsanopoulos A.N. Vector filtering for color imaging. IEEE Signal Processing Magazine 22 (2005) 74-86
35. Lukac R., Smolka B., Plataniotis K.N., and Venetsanopoulos A.N. Vector sigma filters for noise detection and removal in color images. Journal of Visual Communication and Image Representation 1 (2006) 1-26
36. Lukac R., Fischer V., Motyl G., and Drutarovsky M. Adaptive video filtering framework. International Journal of Imaging Systems and Technology 14 (2004) 223-237
37. Morillas S., Gregori V., Peris-Fajarnes G., and Latorre P. A fast impulsive noise color image filter using fuzzy metrics. Real-Time Imaging 11 (2005) 417-428
38. M. Muneyasu, N. Nishi, T. Hinamoto, A new adaptive center weighted median filters using counter propagation networks, in: Proceedings of IEEE 6th International Workshop on Intelligent Signal Processing and Communication Systems, 1998, pp. 103-107.
39. Oflazer K. Design and implementation of a single chip 1-D median filter. IEEE Transactions on Acoustic, Speech, Signal Processing 31 (1983) 1164-1168
40. Ohno S., and Sakai H. Convergence behavior of the LMS algorithm in subband adaptive filtering. Signal Processing 81 (2001) 1053-1059
41. Qin Z., and Lawry J. Decision tree learning with fuzzy labels. Information Sciences 172 (2005) 91-129
42. Sayood K. Introduction to Data Compression. second ed. (2000), Morgan Kaufman
43. Smolka B., and Chydzinski A. Fast detection and impulsive noise removal in color images. Real-Time Imaging 11 (2005) 389-402
44. Sun T., and Neuvo Y. Detail-preserving median based filters in image processing. Pattern Recognition Letters 15 (1994) 341-347
45. Weickert J. Applications of nonlinear diffusion in image processing and computer vision. Acta Mathematica Universitatis Comenianae 70 (2001) 135-145
46. Yang G.Z., Burger P., Firmin D.N., and Underwood S.R. Structure adaptive anisotropic filtering. Image and Vision Computing 14 (1995) 135-145
47. Yin L., Yang R., Gabbouj M., and Neuvo Y. Weighted median filters: a tutorial. IEEE Transactions on Circuits and Systems 43 (1996) 157-192