Abstract
Impulse noise reduction from images is an indispensable research issue in the area of image processing. In this paper, we are proposing a fast adaptive fuzzy filter for restoring the pixels that are damaged through salt and pepper noise or impulse noise. The process of filtering consists of three stages. In first stage, we are concentrating on identifying the window dimension for processing pixel using fuzzy detector. In second stage, noise effected pixel can be identified with help of mathematical 3N rule and in the last stage, we restored noise pixel with unsymmetric trimmed mean value. In restoration process, identification of noise pixel is a complex task. This can be simplified in our proposed filtering method with effective performance of 3N rule. Experiments on standard image and medical image sets were conducted to compare our restoration algorithm with two previous competitors. The results show that our method is superior to existing algorithms considering PSNR and elapsed time. The proposed method also indicates to be strong to high ranges of noise, as excessive as 90% with conserving the key details of the image. And it is useful in many applications.
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
References
R. C. Gonzalez and R. E. Woods, “Digital Image Processing”, Prentice Hall 2002.
W. K. Pratt, “Median filtering,” Tech. Rep., Image Proc. Inst., Univ. Southern California, Los Angeles, Sep. 1975.
I. Pitas and A. Venetsanopou, Nonlinear Digital Filters: Principles and Application. Norwell, MA: Kluwer, 1990.
J. Astola and P. Kuosmanen, Fundamentals of Nonlinear Digital Filtering. Boca Raton, FL: CRC, 1997.
D. R. K. Brownrigg, “The weighted median filter,” ACM Commun., vol. 27, no. 8, pp. 807–818, Aug. 1984.
S. J. Ko and Y. H. Lee, “Center weighted median filters and their applications to image enhancement,” IEEE Trans. Circuits Syst., vol. 38, no. 9, pp. 984–993, Sep. 1991.
T. Sun and Y. Neuvo, “Detail-preserving median based filters in image Processing,” Pattern Recognit. Lett., vol. 15, pp. 341–347, 1994.
D. Florencio and R. Schafer, “Decision-based median filter using local signal statistics,” in Proc. SPIE Int. Symp. Visual Communications Image Processing, Chicago, Sept. 1994.
S. Zhang and M. A. Karim, “A new impulse detector for switching median filters,” IEEE Signal Process. Lett., vol. 9, no. 11, pp. 360–363, Nov. 2002.
How-Lung Eng and Kai-Kuang Ma, “Noise adaptive soft-switching median filter”, IEEE Transactions on Image Processing, Vol. 10, No 2, August 2002.
P. E. Ng and K. K. Ma, “A switching median filter with boundary discriminative noise detection for extremely corrupted images”, IEEE Transactions on Image Processing, Vol. 15, No. 6, pp. 1506–1516, 2006.
K. S. Srinivasan and D. Ebenezer “A new fast and efficient decision-based algorithm for removal of high-density impulse noises”, IEEE Signal Process. Lett., vol. 14, no. 3, pp. 189–192 2007.
D. Y. Li and Y. Du Artificial Intelligent With Uncertainty, 2007: CRC Press.
Zhe Zhou, “Cognition and Removal of Impulse Noise With Uncertainty”, IEEE Transactions on image processing, vol. 21, no. 7, pp. 3157–3167, July 2012.
Sema Koc Kayhan, “An effective 2-stage method for removing impulse noise in images”, J. Vis Commun. Image R, Vol 25, pp. 478–486 2014.
P. S. Windyga, “Fast impulsive noise removal,” IEEE Trans. Image Process., vol. 10, no. 1, pp. 173–179, Jan. 2001.
I. Aizenberg and C. Butakoff, “Effective impulse detectors based on rank-order criteria,” IEEE Signal Process. Lett., vol. 11, no. 3, pp. 363–366, Mar. 2004.
H. Hwang and R. A. Haddad, “Adaptive Median Filters: New Algorithms and Results”, IEEE Transactions on Image Processing, Vol. 4, No. 4, April 1995.
Z. Wang and D. Zhang, “Progressive switching median filter for the removal of impulse noise from highly corrupted images,” IEEE Trans. Circuits Syst. II, Analog Digit. Signal Process., vol. 46, no. 1, pp. 78–80, Jan. 1999.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Vijaya Kumar, S., Nagaraju, C. (2018). A Fast Adaptive Fuzzy Unsymmetric Trimmed Mean Filter for Removal of Impulse Noise from Digital Images. In: Mandal, J., Saha, G., Kandar, D., Maji, A. (eds) Proceedings of the International Conference on Computing and Communication Systems. Lecture Notes in Networks and Systems, vol 24. Springer, Singapore. https://doi.org/10.1007/978-981-10-6890-4_12
Download citation
DOI: https://doi.org/10.1007/978-981-10-6890-4_12
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-6889-8
Online ISBN: 978-981-10-6890-4
eBook Packages: EngineeringEngineering (R0)