A New Efficient Impulse Noise Detection based on Rank Estimation
2
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
In this paper, we present a new impulsive noise detection technique. To remove the impulse noise without detail loss, only corrupted pixels must be filtered. In order to identify the corrupted pixels, a new impulse detector based on rank and value estimations of the current pixel is proposed. Based on the rank and value estimations of the current pixel, the new proposed method provides excellent statistics for detecting an impulse noise while reducing the probability of detecting image details as impulses. The proposed detection is efficient and can be used with any noise removal filter. Simulation results show that the proposed method significantly outperforms many other well-known detection techniques in terms of image restoration and noise detection.
Abstract
In this paper, we present a new impulsive noise detection technique. To remove the impulse noise without detail loss, only corrupted pixels must be filtered. In order to identify the corrupted pixels, a new impulse detector based on rank and value estimations of the current pixel is proposed. Based on the rank and value estimations of the current pixel, the new proposed method provides excellent statistics for detecting an impulse noise while reducing the probability of detecting image details as impulses. The proposed detection is efficient and can be used with any noise removal filter. Simulation results show that the proposed method significantly outperforms many other well-known detection techniques in terms of image restoration and noise detection.
참고문헌 (16)
- D.R.K. Brownrigg, "The weighted median filter", Comm. Ass. Comput. Mach, 27(8), pp.807~818 (1984)
- S.J. Ko, "Center weighted median filters and their applications to image enhancement", IEEE Trans. Circuits Syst, 38, pp.984~993 (1991)
- R.C. Hardie, "Rank conditioned rank selection filters for signal processing", IEEE Trans. Signal Process, 3(2), pp.192~206 (1994), pp.192-206
- A.B. Hamza, "Removing noise and preserving details with relaxed median filters", J. Math. Imaging and Vision, 11(2), pp.161~177 (1999)
- E. Abreu, "A new efficient approach for the removal of impulse noise from highly corrupted images", IEEE Trans. Image Process, 5(6), pp.1012~1025 (1996)
- Z. Wang, "Progressive switching median filter for the removal of impulse noise from highly corrupted images", IEEE Trans. Circuits Syst, 46(1), pp.78~80 (1999)
- R. Garnett, "A universal noise removal algorithm with an impulse detector", IEEE Trans. Image Process, 14(11), pp.1747~1754 (2005)
- W.-Y. Han, "Minimum-maximum exclusive mean (MMEM) filter to remove impulse noise from highly corrupted images", Electron. Lett, 33(2), pp.124~125 (1997)
- T.-C. Lin, "Salt-pepper impulse noise detection and removal using multiple thresholds for image restoration", J. Inform. Science and Eng, 22(1), pp.189~198 (2006)
- E. Abreu, "Signal-dependent rank-ordered mean filters,in Nonlinear Image Processing, ed. S.K. Mitra and G.L. Sicuranza" (2000), Academic Press
- K.M. Singh, "Rank ordered mean filter for removal of impulse noise from images", IEEE Inter. Confer. Industrial Tech., 통권 : 2, pp.980~985 (2002)
- I. Aizenberg, "Effective impulse detector based on rank-order criteria", IEEE Signal Process. Letters, 11(3), pp.363~366 (2004)
- W. Luo, "A new efficient impulse detection algorithm for the removal of impulse noise", IEICE Trans. Fundamentals, E88-A(10), pp.2579~2586 (2005)
- J. Oh, "Minimum-maximum exclusive interpolation filter for image denoising", IEICE Trans. Fundamentals, E90-A(6), pp.1228~1231 (2007)
- G. Pok, "Selective removal of impulse noise based on homogeneity level information", IEEE Trans. Image Process, 12(1), pp.85~92 (2003)
- M.E. Yuksel, "Detail preserving restoration of impulse noise corrupted images by a switching median filter guided by a simple neuro-fuzzy network", EURASIP J. Applied Signal Process, pp.2451~2461 (2004)