Abstract
In this paper problem of impulse noise removal is considered. Specifically, modifications of ranked order adaptive median filter (RAMF) are proposed. RAMF is popular, well established and effective switching median filter for denoising images corrupted by impulse noise. However, the modifications proposed in this paper significantly improve its results, especially in case of highly corrupted images. Results of denosing of images under a wide range of noise corruption (5-95%) using the original and the modified ranked order median filter are presented, compared and discussed. Comparison is made by means of PSNR and SSIM index.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Arce, G.R., Gallagher, N.C., Nodes, T.: Median filters: theory and applications. In: Huang, T. (ed.) Advances in Computer Vision and Image Processing. JAI Press, CT (1986)
Astola, J., Kuosmanen, P.: Fundamentals of nonlinear digital filtering. CRC Press, USA (1997)
Chen, T., Wu, H.R.: Adaptive impulse detection using center-weighted median filters. IEEE Signal Processing Letters 8(1), 1–3 (2001)
Gil, J., Werman, M.: Computing 2-D min, median, and max filters. IEEE Trans. Pattern Analysis and Machine Intelligence 15(5), 504–507 (1993)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing. Prentice Hall, USA (2007)
Guangjin, Z., Jiegu, L.: Some problems of 2D morphological and median filters. Journal of Shanghai University (English Edition) 1(3), 245–248 (1997)
Hwang, H., Haddad, R.A.: Adaptive median filters: New algorithms and results. IEEE Trans. Image Processing 4(4), 499–502 (1995)
Lin, H.M., Wilson, A.N.: Median filters with adaptive length. IEEE Trans. Circuits and Systems 35(6), 675–690 (1988)
Ng, P.-E., Ma, K.-K.: A switching median filter with boundary discriminative noise detection for extremely corrupted images. IEEE Trans. Image Processing 15(6), 1506–1516 (2006)
Pitas, I., Venetsanopoulos, A.N.: Order statistics in digital image processing. Proc. IEEE 80(12), 1893–1921 (1992)
Vijaykumar, V.R., Vanathi, P.T., Kanagasabapathy, P., Ebenezer, D.: High density impulse noise removal using robust estimation based filter. IAENG International Journal of Computer Science 35(3) (2008), http://www.iaeng.org/IJCS/issues_v35/issue_3/index.html (accessed November 2010)
Wang, Z., Bovik, A.C.: Mean squared error: love it or leave it. IEEE Signal Proc. Magazine 26(1), 98–117 (2009)
Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Processing 13(4), 600–612 (2004)
Yin, L., Yang, R., Gabbouj, M., Neuvo, Y.: Weighted median filters: a tutorial. IEEE Trans. Circuits and Systems 43(3), 157–192 (1996)
Zvonarev, P.S., Apalkov, I.V., Khryashchev, V.V., Reznikova, I.V.: Neural network adaptive switching median filter for the restoration of impulse noise corrupted images. In: Kamel, M.S., Campilho, A.C. (eds.) ICIAR 2005. LNCS, vol. 3656, pp. 223–230. Springer, Heidelberg (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Fabijańska, A. (2011). Modified Ranked Order Adaptive Median Filter for Impulse Noise Removal. In: Burduk, R., Kurzyński, M., Woźniak, M., Żołnierek, A. (eds) Computer Recognition Systems 4. Advances in Intelligent and Soft Computing, vol 95. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20320-6_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-20320-6_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-20319-0
Online ISBN: 978-3-642-20320-6
eBook Packages: EngineeringEngineering (R0)