Abstract
In this paper, a hybrid image restoration technique based on fuzzy logic and directional weighted median is presented. The proposed technique consists of noise detection and fuzzy filtering processes to detect and remove uniform (random-valued) impulse noise while preserving the image details efficiently. In order to preserve image details such as edges and texture information, a two-stage robust noise detection is presented in this paper. Pixels detected as noisy by both the noise detection stages are considered for noise removal by the fuzzy filtering process, which utilizes the direction based weighted median to construct fuzzy membership function, which is the main contributing factor in noise removal and detail preservation. Extensive experimentation shows that the proposed technique performs significantly better than state-of-the-art filters based on peak signal-to-noise ratio, structural similarity index measure and subjective evaluation criteria.
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References
Gonzalez RC, Woods RE (2002) Digital image processing, 2nd edn. Pearson Education Inc, New Jersey
Tukey JW (1971) Exploratory data analysis. Addison-Wesley, Reading
Astola J, Kuosmanen P (1997) Fundamentals of nonlinear digital filtering. CRC Press, Boca Raton
Pitas I, Venetsanopoulos A (1990) Nonlinear digital filters: principles and application. Kluwer, Norwell, MA
Han WY, Lin JC (1997) Minimum–maxmum exclusive mean (MMEM) filter to remove impulse noise from highly corrupted image. Electron Lett 33: 124–125
Lee KC, Song HJ, Sohn KH (1998) Detection-estimation based approach for impulsive noise removal. Electron Lett 34: 449–450
Arce G, Foster R (1989) Detail-preserving ranked-order based filter for image processing. IEEE Trans Acoust Speech Signal Process 37: 83–98
Brownrigg D (1984) The weighted median filter. Commun Assoc Comput 27(8): 807–818
Ko SJ, Lee SJ (1991) Center weighted median filters and their applications to image enhancement. IEEE Trans Circuits Syst 15(9): 984–993
Eng HL, Ma KK (2001) Noise adaptive soft-switching median filter. IEEE Trans Image Process 10(2): 242–251
Dong Y, Xu S (2007) A new directional weighted median filter for removal of random-valued impulse noise. IEEE Signal Process Lett 14(3): 193–196
Wang JH, Liu WJ, Lin LD (2002) Histogram-based fuzzy filter for image restoration. IEEE Trans Syst Man Cybern 32(2): 230–238
Lee C-S, Guo S-M, Hsu C-Y (2004) A Novel fuzzy filter for impulse noise removal. Lecture Notes in Computer Science, pp 375–380, 3174/2004
Lee C-S, Guo S-M, Hsu C-Y (2005) Genetic-based fuzzy image filter and its applications to image processing. IEEE Trans Syst Man Cybern 35(4): 694–711
Hussain A, Jaffar MA, Mirza AM, Chaudhry A (2009) Detail preserving fuzzy filter for impulse noise removal. Int J Innovative Comput Inf Control 12(5)
Schulte S, Nachtegael M, Witte V, Van der Weken D, Kerre EE (2006) A fuzzy impulse noise detection and reduction method. IEEE Trans Image Process 15(5): 1153–1162
Schulte S, de Witte V, Nachtegael M, Van der Weken D, Kerre EE (2007) Fuzzy random impulse noise reduction method. Fuzzy Sets Syst 158(3): 270–283
Petrovic’ NI, Crnojevic V (2008) Universal impulse noise filter based on genetic programming. IEEE Trans Image Process 17(7): 1109–1120
Schulte S, Witte V, Nachtegael M, Van der Weken D, Kerre EE (2007) Histogram-based fuzzy colour filter for image restoration. Image Vis Comput 25(9): 1377–1390
Wang Z, Bovik AC, Sheikh HR, Simocelli EP (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 3(13): 1–14
Resconi G, Kovalerchuk B (2009) Agents’ model of uncertainty. Knowl Inf Syst 18(2): 213–229
Senthil Arumugam M, Rao MVC, Chandramohan A (2008) A new and improved version of particle swarm optimization algorithm with global–local best parameters. Knowl Inf Syst 16(3): 331–357
Saha S, Bandyopadhyay S (2009) A new multiobjective clustering technique based on the concepts of stability and symmetry. Knowl Inf Syst. doi:10.1007/s10115-009-0204-4
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Hussain, A., Jaffar, M.A. & Mirza, A.M. A hybrid image restoration approach: fuzzy logic and directional weighted median based uniform impulse noise removal. Knowl Inf Syst 24, 77–90 (2010). https://doi.org/10.1007/s10115-009-0236-9
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DOI: https://doi.org/10.1007/s10115-009-0236-9