Abstract
In this paper, we propose a Noise Detection Fuzzy (NDF) filter, to achieve improved filtering performance in terms of effectiveness in removing salt-and-pepper noise while preserving image details. It operates in a moving window where the update value of the central pixel is a function of the median of the pixels in the window. The proposed NDF filter consists of three sequential stages. Firstly, a noise-detection scheme is developed to classify each pixel to be uncorrupted pixel, or otherwise. Secondly, if a pixel is suspected to be noise, it is not used for determining the update value of other pixels. Thus we can prevent noise pixels from distorting the “correct” update value. Thirdly, the fuzzy filter part will then adaptively assign weights to the recorded pixel values to produce the central pixel update value. Experimental results show that our NDF filter outperforms other standard median based techniques.
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References
Pitas, I., Venetsanopoulos, A.N.: Nonlinear digital filters: Principles and Applications. Kluwer Academic Publishers, Dordrecht (1990)
Mitra, S.K., Sicuranza, G. (eds.): Nonlinear Image Processing. Academic Press, London (2000)
Taguchi, A., Meguro, M.: Adaptive L-filters based on fuzzy rules. In: Proc. IEEE Int. Symp. Circuits Systems, ISCAS 1995, Seattle, WA, April 15, pp. 961–964 (1995)
Choi, Y.S., Krishnapuram, R.: A robust approach to image enhancement based on fuzzy logic. IEEE Trans. Image Processing 6(6), 808–825 (1997)
Hanmandlu, M., Jha, D.: An optimal fuzzy system for color image enhancement. IEEE Transactions on Image Processing 15(10), 2956–2966 (2006)
Tukey, J.W.: Exploratory Data Analysis. Addison-Wesley, Menlo Park (1971)
Tukey, J.W.: Nonlinear (nonsuperposable) methods for smoothing data. Congr. Res. EASCON, 673 (1974)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn. Prentice Hall, Upper Saddle River (2002)
Russo, F.: A technique for image restoration based on recursive processing and error correction. In: Proceedings of the 17th IEEE Instrumentation and Measurement Technology Conference (IMTC 2000), vol. 3, pp. 1232–1236 (2000)
Nieminen, A., Heinonen, P., Neuvo, Y.: A new class of detail-preserving filters for image processing. IEEE Trans. Pattern Anal. Mach. Intell. 9(1), 74–90 (1987)
ben Hamza, A., Luque-Escamilla, P.L., Aroza, J.M., Roldan, R.R.: Removing noise and preserving details with relaxed median filters. Journal of Mathematical Imaging and Vision 11(2), 161–177 (1999)
Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: From error visibility to structural similarity. IEEE Transactions on Image Processing 13(4), 600–612 (2004)
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Kam, H.S., Tan, W.H. (2009). Noise Detection Fuzzy (NDF) Filter for Removing Salt and Pepper Noise. In: Badioze Zaman, H., Robinson, P., Petrou, M., Olivier, P., Schröder, H., Shih, T.K. (eds) Visual Informatics: Bridging Research and Practice. IVIC 2009. Lecture Notes in Computer Science, vol 5857. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05036-7_45
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DOI: https://doi.org/10.1007/978-3-642-05036-7_45
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-05035-0
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