A new fuzzy additive noise reduction method

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4633 LNCS, Issue , 2007, Pages 12-23

  Schulte, Stefan ^a   De Witte, Valérie ^a   Nachtegael, Mike ^a   Mélange, Tom ^a   Kerre, Etienne E ^a  

^a GHENT UNIVERSITY   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE FILTERS; ADDITIVE NOISE; FUZZY LOGIC; GAUSSIAN NOISE (ELECTRONIC); PIXELS;

COLOR IMAGES; COMPLEMENTARY FILTER; IMAGE STRUCTURES;

NOISE ABATEMENT;

EID: 37849026517     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-74260-9_2     Document Type: Conference Paper

References (26)

1. Guo, S.M., Lee, C.S., Hsu. C.Y.: An intelligent image agent based on softcomputing techniques for color image processing. Expert Systems with Applications 28, 483-494 (2005)
2. Lucchese, L., Mitra, S.K.: A New Class of Chromatic Filters for Color Image Processing: Theory and Applications. IEEE Transactions on Image Processing 13(4), 534-543 (2004)
3. Plataniotis, K.N., Androutsos, D., Venetsanopoulos, A.N.: Colour image processing using fuzzy vector directional filters. In: Proceedings of the IEEE International Workshop on Nonlinear Signal and Image Processing, pp. 535-538. IEEE Computer Society Press, Los Alamitos (1995)
4. Plataniotis, K.N., Venetsanopoulos, A.N.: Color Image Processing and Applications. Springer, Berlin, Germany (2000)
5. Vertan, C., Buzuloiu, V.: Fuzzy nonlinear filtering of color images. In: Kerre, E.E., Nachtegael, M. (eds.) Fuzzy Techniques in Image Processing, vol. 52, pp. 248-264. Springer Physica Verlag, Heidelberg (2000)
6. Arce, G.R., Foster, R.E.: Detail-preserving ranked-order based filters for image processing. IEEE Transactions on Acoustics, Speech, and Signal Processing 37(1), 83-93 (1989)
7. Lukac, R., Smolka, B., Martin, K., Plataniotis, K.N., Venetsanopoulos, A.N.: Vector filtering for color imaging. IEEE Signal Processing Magazine 22(1), 74-86 (2005)
8. Hore, S., Qiu, B., Wu, H.R.: Improved vector filtering for color images using fuzzy noise detection. Optical Engineering 42(6), 1656-1664 (2003)
9. Tsai, H.H., Yu, P.T.: Genetic-based fuzzy hybrid multichannel filters for color image restoration. Fuzzy Sets and Systems 114(2), 203-224 (2000)
10. Takagi, T., Sugeno, M.: Fuzzy identification of systems and its applications to modeling and control. IEEE Transactions on Systems Man and Cybernetic 15, 116-132 (1985)
11. Kerre, E.E.: Fuzzy Sets and Approximate Reasoning. Xian Jiaotong University Press, Xian Jiaotong (1998)
12. Zadeh, L.A.: Fuzzy Sets. Information and Control 8(3), 338-353 (1965)
13. Cornelis, C., Deschrijver, G., Kerre, E.E.: Classification of intuitionistic fuzzy implicators: an algebraic approach. In: Proceedings of the 6th Joint Conference on Information Sciences, pp. 105-108 (2002)
14. Kwan, H.K.: Fuzzy filters for noise reduction in images. In: Nachtegael, M., Van der Weken, D., Van De Ville, D., Kerre, E.E. (eds.) Fuzzy Filters for Image Processing, vol. 122, pp. 25-53. Springer Physica Verlag, Heidelberg (2003)
15. Arakawa, K.: Median filter based on fuzzy rules and its application to image restoration. Fuzzy Sets and Systems 77, 3-13 (1996)
16. Morillas, S., Gregori, V., Sapena, A.: Fuzzy Bilateral Filtering for Color Images. In: Campilho, A., Kamel, M. (eds.) ICIAR 2006. LNCS, vol. 4141, pp. 138-145. Springer, Heidelberg (2006)
17. Van De Ville, D., Nachtegael, M., Van der Weken, D., Kerre, E.E., Philips, W.: Noise reduction by fuzzy image filtering. IEEE Transactions on Fuzzy Systems 11, 429-436 (2003)
18. Farbiz, F., Menhaj, M.B.: A fuzzy logic control based approach for image filtering. In: Kerre, E.E., Nachtegael, M. (eds.) Fuzzy Techniques in Image Processing, vol. 52, pp. 194-221. Springer Physica Verlag, Heidelberg (2000)
19. Romberg, J.K., Choi, H., Baraniuk, R.G., Kingbury, N.: Multiscale classification using complex wavelets and hidden Markov tree models. In: ICIP. Proceedings of the IEEE International Conference on Image Processing, pp. 371-374. IEEE Computer Society Press, Los Alamitos (2000)
20. Romberg, J.K., Choi, H., Baraniuk, R.G.: Bayesian tree-structured image modeling using wavelet-domain hidden Markov models. IEEE Transactions on Image Processing 10(7), 1056-1068 (2001)
21. Dabov, K., Foi, A., Katkovnik, V., Egiazarian, K.: Image Denoising with Block-Matching and 3D Filtering. In: Proceedings of SPIE Electronic Imaging: Algorithms and Systems, Neural Networks, and Machine Learning, pp. 354-365 (2006)
22. Portilla, J., Strela, V., Wainwright, M., Simoncelli, E.: Image denoising using gaussian scale mixtures in the wavelet domain. IEEE Transactions on Image Processing 12, 1338-1351 (2003)
23. Şendur, L., Selesnick, I.W.: Bivariate shrinkage functions for wavelet-based denoising exploiting interscale dependency. IEEE Transactions on Signal Processing 50, 2744-2756 (2002)
24. Hirakawa, K., Parks, T.W.: Image Denoising for Signal-Dependent Noise. In: Proceedings of the IEEE Acoustics, Speech, and Signal Processing, pp. 18-23. IEEE Computer Society Press, Los Alamitos (2005)
25. Schulte, S., Huysmans, A., Pižurica, A., Kerre, E.E., Philips, W.: A new fuzzy-based wavelet shrinkage image denoising technique. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds.) ACIVS 2006. LNCS, vol. 4179, pp. 12-23. Springer, Heidelberg (2006)
26. Gilboa, G., Zeevi, Y.Y., Sochen, N.A.: Complex diffusion processes for image filtering. In: Kerckhove, M. (ed.) Scale-Space 2001. LNCS, vol. 2106, pp. 299-307. Springer, Heidelberg (2001)