A new method for impulsive noise suppression from highly distorted images by using Anfis

Engineering Applications of Artificial Intelligence

Volumn 17, Issue 5, 2004, Pages 519-527

  Beşdok, Erkan ^a  

^a ERCIYES UNIVERSITY   (Turkey)

Author keywords

Anfis; Delaunay triangles; Finite element based computing; Impulsive noise

Indexed keywords

COMPUTATIONAL METHODS; COMPUTER SIMULATION; FINITE ELEMENT METHOD; IMAGE ANALYSIS; INTERFERENCE SUPPRESSION; ITERATIVE METHODS; NONLINEAR FILTERING;

ANFIS; DELAUNAY TRIANGLES; FINITE-ELEMENT-BASED COMPUTING; IMAGE DISTORTION;

IMPULSE NOISE;

EID: 19244382035     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.engappai.2004.03.009     Document Type: Article

References (27)

1. Abreu E., et al. A new efficient approach for the removal of impulse noise from highly corrupted images. IEEE Transactions on Image Processing. 5(6):1996;1012-1025.
2. Breveglieri L., Piuri V. Digital median filters. Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology. 31:2002;191-206.
3. Chen T., Wu H.R. A new class of median based impulse rejecting filters. IEEE International Conference on Image Processing. 1:2000;916-919.
4. Chen T., et al. Adaptive impulse detection using center weighted median filters. IEEE Signal Processing Letters. 8(1):2001;1-3.
5. Christopher L.B., Abdelhak M.Z. Testing for impulsive behavior. a bootstrap approach Digital Signal Processing. 11(2):2001;120-132.
6. Jang J.S.R. ANFIS: adaptive-network-based fuzzy inference systems. IEEE Transactions on Systems, Man, and Cybernetics. 23(03):1993;665-685.
7. Jang J.S.R., Gulley N. The Fuzzy Logic Toolbox for Use with MATLAB. 1995;The Mathworks, Inc. New York.
8. Jang J.S.R., Sun C.T. Neuro-fuzzy modeling and control. Proceedings of the IEEE. 83:1995;378-406.
9. Jang, J.S.R., Sun, C.T., Mizutani, E., 1996. Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence. Prentice-Hall, 1st edition.
10. Lin H., Willson A.N. Median filter with adaptive length. IEEE Transactions on Circuits and Systems. 35:1988;675-690.
11. MathWorks, 2002. MATLAB the language of technical computing. MATLAB Function Reference, New York, The MathWorks, Incorporation.
12. Muneyasu M., Nishi N., Hinamoto T. A new adaptive center weighted median filter using counter propagation networks. Journal of the Franklin Institute. 337:2000;631-639.
13. Nodes T.A., Gallagher N.C. Jr. Median filters. some modifications and their properties IEEE Transactions on Acoustics, Speech, Signal Processing. 30(5):1982;739-746.
14. Palisade Corp., 2002. Guide to using Bestfit, Distribution Fitting for Windows, Version 4.5.
15. Russo F., Ramponi G. A fuzzy filter for images corrupted by impulse noise. IEEE Signal Processing Letters. 6(3):1996;168-170.
16. Spiegel M.R., Schiller J.J., Srinivasan R.A. Schaum's Outline of Probability and Statistics. 2000;McGraw-Hill, New York.
17. Stephens M.A. EDF statistics for goodness of fit and some comparisons. Journal of the American Statistical Association. 69:1974;730-737.
18. Studer, L., Masulli, F., 1996. On the structure of a neuro-fuzzy system to forecast chaotic time series. Proceedings of the First International Symposium on Neuro-Fuzzy Systems, AT'96, pp. 103-110.
19. Sugeno M., Kang G.T. Structure identification of fuzzy model. Fuzzy Sets and Systems. 28:1998;15-33.
20. Sun T., Neuvo Y. Detail-preserving median based filters in image processing. Pattern Recognition Letters. 15:1994;341-347.
21. Takagi, T., Sugeno, M., 1983. Derivation of fuzzy control rules from human operator's control actions. Proceedings of the IFAC Symposium on Fuzzy Information, Knowledge Representation and Decision Analysis, pp. 55-60.
22. Tukey, J.W., 1974. Nonlinear (nonsuperposable) methods for smoothing data. Congress Records EASCON'74, 673pp.
23. Wang J.H., Liu W.J., Lin L.D. Histogram-based fuzzy filter for image restoration. IEEE Transactions on Systems, Man, and Cybernetics, Part B. 32(2):2002;230-238.
24. Wang Z., Zhang D. Progressive switching median filter for the removal of impulse noise from highly corrupted images. IEEE Transactions on Circuits and Systems-II: Analog and Digital Signal Processing. 46(1):1999;78-80.
25. Watson, D.F., 1994. Contouring: A Guide to the Analysis and Display of Spacial Data. Pergamon, New York, pp. 101-161.
26. Yang, T.Y., 1986. Finite Element Structural Analysis. Prentice-Hall, Englewood Cliffs, NJ, pp. 446-449.
27. Yüksel M.E., Baştürk A. Efficient removal of impulse noise from highly corrupted digital images by a simple neuro-fuzzy operator. AEU International Journal of Electronics and Communications. 57(3):2003;214-219.