A fast novel algorithm for salt and pepper image noise cancellation using cardinal B-splines

Signal, Image and Video Processing

Volumn 7, Issue 6, 2013, Pages 1145-1157

  Jayasree, P Syamala ^a   Raj, Paru ^a   Kumar, Pradeep ^a   Siddavatam, Rajesh ^a   Ghrera, S P ^a  

^a JAYPEE UNIVERSITY OF INFORMATION TECHNOLOGY   (India)

Author keywords

Cardinal B splines; Image denoising; Salt and pepper noise

Indexed keywords

B SPLINES; BETTER PERFORMANCE; CARDINAL B-SPLINE; COMPACT SUPPORT; INTERPOLATION PROPERTIES; NOVEL ALGORITHM; SALT AND PEPPERS; SALT-AND-PEPPER NOISE;

ALGORITHMS; IMAGE DENOISING; SHIP PROPELLERS; SIGNAL DENOISING; SPURIOUS SIGNAL NOISE;

INTERPOLATION;

EID: 84885899618     PISSN: 18631703     EISSN: 18631711     Source Type: Journal    
DOI: 10.1007/s11760-012-0368-3     Document Type: Article

References (26)

1. Michael U.: Splines: a perfect fit for signal and image processing. IEEE Signal Process. Mag. 16(6), 24-38 (1999).
2. Jaiswal, T., Siddavatam, R.: Image noise cancellation by lifting filter using second generation wavelets. In: Proceedings of IEEE International Conference on Advances in Recent Technologies in Communication and Computing, pp. 667-671. Kerala, India, 27-28 Oct. (2009).
3. Siddavatam, R., Sandeep, K., Mittal, R. K.: A fast progressive image sampling using lifting scheme and non-uniform B-Splines. In: Proceedings of IEEE International Symposium on Industrial Electronics ISIE-07, pp. 1645-1650. Vigo, Spain, 4-7 June (2007).
4. Sun T., Neuvo Y.: Detail-preserving median based filters in image processing. Pattern Recogn. Lett. 15, 341-347 (1994).
5. Luo W.: An efficient detail-preserving approach for removing impulse noise in images. In: IEEE Signal Process. Lett. 13(7), 413-416 (2006).
6. Raymond H. C., Chung-Wa H., Mila N.: Salt and peeper noise removal by median-type noise detectors and detail-preserving regularization. In: IEEE Trans. Image Process. 14(10), 1479-1485 (2005).
7. Pok G., Liu J. C., Nair A. S.: Selective removal of impulse noise based on homogeneity level information. In: IEEE Trans. Image Process. 12(1), 85-92 (2003).
8. Chen T., Wu H. R.: Application of partition-based median type filters for suppressing noise in images. In: IEEE Trans. Image Process. 10(6), 829-836 (2001).
9. Chan R. H., Hu C., Nikolova M.: An iterative procedure for removing random-valued impulse noise. In: IEEE Signal Process. Lett. 11(12), 921-924 (2004).
10. Wang Z., Bovik A. C., Sheikh H. R., Simoncelli E. P.: Image quality assessment: from error visibility to structural similarity. In: IEEE Trans. Image Process. 13(4), 600-612 (2004).
11. Swelden W.: The lifting scheme: a construction of second generation wavelets. SIAM J. Math. Anal. 29(2), 511-546 (1998).
12. Lee J. S.: Digital image enhancement and filtering by use of local statistics. In: IEEE Trans. Pattern Anal. Mach. Intell. PAMI 2, 165-168 (1980).
13. Kuan D. T., Sawchuk A. A., Strand T. C., Chavel P.: Adaptive noise smoothing filter for images with signal-dependent noise. In: IEEE Trans. Pattern Anal. Mach. Intell. PAMI 7(2), 165-177 (1985).
14. Bernstein R.: Adaptive nonlinear filters for simultaneous removal of different kinds of noise in images. In: IEEE Trans. Circ. Syst. CAS 34(11), 1275-1291 (1987).
15. Sun X. Z., Venetsanopoulos A. N.: Adaptive schemes for noise filtering and edge detection by use of local statistics. In: IEEE Trans. Circ. Syst. CAS 35(1), 57-69 (1988).
16. Fahmy M. F., Gamal Fahmy, Fahmy O. F.: B-spline wavelets for signal denoising and image compression. Springer J. Signal Image Video Process. 5(2), 141-153 (2009).
17. Jayasree P. S., Kumar P., Siddavatam R., Ravi kant V.: Salt-and-pepper noise removal by adaptive median-based lifting filter using second-generation wavelets. Springer J. Signal Image Video Process. 5(2), 1-8 (2011).
18. Ognyan K.: Multivariate Polysplines: Applications to Numerical and Wavelet Analysis. Academic Press, London (2001).
19. Biswas S., Lovell B. C.: Bézier and Splines in Image Processing and Machine Vision. Springer, London (2008).
20. Bartels R. H., Beatty J. C., Barsky B. A.: An Introduction to Splines for Use in Computer Graphics and Geometry Modelling. Morgan Kaufmann, Los Altos (1987).
21. Arce G. R., McLoughlin M. P.: Theoretical analysis of the MAX/Median filter. In: IEEE Trans. Acoust. Speech Signal Process. ASSP-35, 60-69 (1987).
22. Gonzalez R. C., Woods R. E.: Digital Image Processing. Prentice Hall, Englewood Cliffs (2006).
23. Michael U., Akram A., Murray E.: Fast B-Spline transforms for continuous image representation and interpolation. In: IEEE Trans. Pattern Anal. Mach. Intell. 13(3), 277-285 (1991).
24. Erik M., Michael U.: A note on cubic convolution interpolation. In: IEEE Trans. Image Process. 12(4), 477-479 (2003).
25. Zhou W., David Z.: Progressive switching median filter for the removal of impulse noise from highly corrupted images. In: IEEE Trans. Circ. Syst. II Analog Digital Signal Process. 46(1), 78-80 (1999).
26. Prasad L., Iyengar S. S.: Wavelet Analysis with Application to Image Processing. CRC Press, Boca Raton (1997).