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Fast and Effective Median Filter Algorithms for Salt and Pepper Noise

Published: 29 July 2020 Publication History

Abstract

For large data of the image processing in the fields of medication or communication, the salt and pepper noise is one of the key problems to affect the quality of the images. In order to obtain stable, fast, and effective filtering algorithms for salt and pepper noise, this paper proposes four filter algorithms, named fast and effective median filter1 (FEMF1), fast and effective median filter2(FEMF2), fast and effective median filter3(FEMF3), and fast and effective median filter4(FEMF4), respectively. FEMF1 uses a second-order differential method to convert the image to a binary matrix to determine the exact location of the broken pixels. It is stable and fast, however it has a sense of noise. FEMF2 and FEMF3 use different directions to search with changing windows. FEMF4 grows square bar window with unlimited growth and has search functions in all directions. FEMF4 costs the lowest time and presents the high quality performance. The running time of the FEMF2 is only slower than that of the FEMF4. Experiment show that FEMF2, FMEF3 and FEMF4 have stable, fast and effective features for low and high noises. These algorithms can be used in engineering applications.

References

[1]
Bovik AC, "Handbook of image and video processing," New York: Academic. (2000).
[2]
Gallager NC,Wise G L, "A Theoretical analysis of the properties of median filter", IEEE Trans. Acous. Speech and Sig. Proc. 29, 6 (1981), 1136--1141.
[3]
D. R. K. Brownrigg, "The weighted median filter," Commun. Ass. Comput. March 27(8), 807-818 (1984).
[4]
Nieminen A, Heinonen P, Y Neuvo, "A new class of detail preserving filters for image processing", IEEE Trans. Pattern Analysis and Machine Intelligence 9, 1 (1987), 74--90.
[5]
Antoni Buades, Bartomeu Coll, Jean-Michel Morel, "A non-local algorithm for image denoising," Proceeding of the IEEE Computer Society Conference On Computer Vision and Pattern Recognition.17, 2 (2005), 60--65.
[6]
Wang Jin, Guo Yanwen,Ying Yiting, "Fast non-local algorithm for image denosing", IEEE International Conference on Image Processing. 1429--1432 (2006).
[7]
Tuekey J. W., "Nonlinear(Nonsuperposal) methods for smoothing data," Proceeding of the IEEE Electronics and Aerospace Systems Conference. 673--681 (1974)
[8]
Ng, P.-E, Ma, K.-K, "A switching median filter with boundary discriminative noise detection for extremely corrupted images", IEEE Trans.Image Process 15, 6(2006), 1506--1516.
[9]
SM. Mahburbur Rahman, Md. Kamurl Hasan, "Wavelet-domain iterative center weighted median filter for image denoising," Signal Processing. 83, 5(2003), 1001--1012.
[10]
K.Somasundaram, P. Shanmugavadivu, "Impulsive noise detection by second-order differential image and noise removal using adaptive nearest neighbourhood filter", AEU-Int. J. Electron. Commun. 62, 6(2008), 472--477.
[11]
Dirk Robinson, Peyman Milan far, "Bias minimizing filter design for gradient-based image registration", Sig. Process. Im. Commun. 20, 7(2005), 554--568.
[12]
Mu-Hsien Hsien, Fan-Chieh Cheng, Mon-Chau Shie, Shanq-Jang Ruan, "Fast and efficient median filter for removing 1-99% levels of salt-and-pepper noise image", Eng. Appl. Artif. Intel. 26, 4(2013), 1333--1338.
[13]
How Lung Eng, Kai Kuang Ma. "Noise adaptive soft switching median filter", IEEE Trans. Image Process. 10, 2 (2001), 242--251.
[14]
Xu H X, Zhu G X, Peng HY, "Adaptive fuzzy switching filter for images corrupted by impulse noise", Patt. Recog. Lett. 25, 15(2004), 1657--1663.
[15]
Zhu Wang, David Zhang, "Progressive switching median filter for removal of impulse noise from highly corrupted images," IEEE Trans. Circuits Syst. II: Analog and Digital Signal Processing 46, 1(1999), 78--80.
[16]
Li Fang and Fan Jinsong, "Salt and pepper noise removal by adaptive median and minimal surface inpainting," CISP'09, 2nd International Congress On image and Signal, 1--5 (2009).
[17]
Kundu Amlan, Vaidyanathan P P, "Application of two-dimensional generalized mean filtering for removal of impulse noise from images," IEEE Trans. Acous. Speech and Sig. Proc. 32, 3(1984), 600--609.
[18]
Saroj K. Meher, Brijraj Singhawat, "An improved recursive and adaptive median filter for high density impulse noise," AEU-Int. J. Electron. Commun. 68(12), 1173--1179 (2014).
[19]
Juan Marcos Ramirez, Jose Luis Paredes, "Recursive myriad-mean filters: Adaptive algorithms and applications," Signal Processing, 139, 1 (2017), 12--24.
[20]
Zhe Zhang, Deqiang Han, Jean Dezert b, Yi Yang, "A new adaptive switching median filter for impulse noise reduction with pre-detection based on evidential reasoning," Signal Processing, 147, 9(2018), 173--189.
[21]
Ugur Erkan, Levent Gökrem, Serdar Enginoglu, "Different applied median filter in salt and pepper noise," Comput. Electr. Eng. 70, 5(2018), 1--10.

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    ICGSP '20: Proceedings of the 4th International Conference on Graphics and Signal Processing
    June 2020
    127 pages
    ISBN:9781450377812
    DOI:10.1145/3406971
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    In-Cooperation

    • University of Macedonia
    • NITech: Nagoya Institute of Technology
    • Zhejiang University: Zhejiang University

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 29 July 2020

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    Author Tags

    1. all directions
    2. changing windows
    3. low and high noise
    4. second-order differential

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