Median filter is widely used to remove impulse noise
without blurring sharp edges. However, when noise level increased,
or with thin edges, median filter may work poorly. This paper
proposes a new filter, which will detect edges along four possible
directions, and then replace noise corrupted pixel with estimated
noise-free edge median value. Simulations show that the proposed
multi-stage directional median filter can provide excellent
performance of suppressing impulse noise in all situations.
[1] W. K. Pratt, Digital Image Processing, John Wiley & Sons, 1978.
[2] T. Sun and Y. Neuvo, "Detail-preserving median based filters in image
processing," Pattern Recognition Letters, vol. 15, no. 4, pp. 341-347,
1994.
[3] D. A. Florencio and R. W. Schafer, "Decision-based median filter using
local signal statistics," in Proceedings of SPIE Symposium, Visual
Communication Image Processing, vol. 2038. pp. 268-275.
[4] Z. Wang and D. Zhang, "Progressive switching median filter for the
removal of impulse noise from highly corrupted images," IEEE
Transactions on Circuits System II, vol. 46, no. 1, pp. 78-80, 1999.
[5] S. Zhang and M. A. Karim, "A new impulse detector for switching
median filters," IEEE Signal Processing Letters, vol. 9, no. 4, pp. 360-
363, 2002.
[6] H. Hwang and R. A. Haddad, "Adaptive median filters: new algorithms
and results," IEEE Transactions on Image Processing, vol. 4, no. 4, pp.
499-502, 1995.
[7] C. Bouman and K. Sauer, "On discontinuity-adaptive smoothness priors
in computer vision," IEEE Transactions on Pattern Analysis and
Machine Intelligence, vol. 17, pp. 576-586, 1995.
[8] T. F. Chan, H. M. Zhou, and R. H. Chan, "A continuation method for
total variation denoising problems," Proceedings of SPIE Symposium on
Advanced Signal Processing: Algorithms, Architectures, and
Implementations, ed. F. T. Luk, pp. 314-325, 1995.
[9] P. Charbonnier, L. Blanc-F'eraud, G. Aubert, and M. Barlaud,
"Deterministic edge-preserving regularization in computed imaging,"
IEEE Transactions on Image Processing, vol. 6, pp. 298-311, 1997.
[10] C. R. Vogel and M. E. Oman, "Fast, robust total variation-based
reconstruction of noisy, blurred images," IEEE Transactions on Image
Processing, vol. 7, pp. 813-824, 1998.
[11] R. H. Chan, C. Ho, and M. Nikolova, "Salt-and-Pepper Noise Removal
by Median-type Noise Detectors and Edge-preserving Regularization,"
IEEE Transactions on Image Processing, vol. 14, pp. 1479-1485, 2005.
[12] Y. Dong and S. Xu. "A New Directional Weighted Median Filter for
Removal of Random-Valued Impulse Noise," IEEE Signal Processing
Letters, vol. 14, no. 3, pp. 193 - 196, 2007.
[1] W. K. Pratt, Digital Image Processing, John Wiley & Sons, 1978.
[2] T. Sun and Y. Neuvo, "Detail-preserving median based filters in image
processing," Pattern Recognition Letters, vol. 15, no. 4, pp. 341-347,
1994.
[3] D. A. Florencio and R. W. Schafer, "Decision-based median filter using
local signal statistics," in Proceedings of SPIE Symposium, Visual
Communication Image Processing, vol. 2038. pp. 268-275.
[4] Z. Wang and D. Zhang, "Progressive switching median filter for the
removal of impulse noise from highly corrupted images," IEEE
Transactions on Circuits System II, vol. 46, no. 1, pp. 78-80, 1999.
[5] S. Zhang and M. A. Karim, "A new impulse detector for switching
median filters," IEEE Signal Processing Letters, vol. 9, no. 4, pp. 360-
363, 2002.
[6] H. Hwang and R. A. Haddad, "Adaptive median filters: new algorithms
and results," IEEE Transactions on Image Processing, vol. 4, no. 4, pp.
499-502, 1995.
[7] C. Bouman and K. Sauer, "On discontinuity-adaptive smoothness priors
in computer vision," IEEE Transactions on Pattern Analysis and
Machine Intelligence, vol. 17, pp. 576-586, 1995.
[8] T. F. Chan, H. M. Zhou, and R. H. Chan, "A continuation method for
total variation denoising problems," Proceedings of SPIE Symposium on
Advanced Signal Processing: Algorithms, Architectures, and
Implementations, ed. F. T. Luk, pp. 314-325, 1995.
[9] P. Charbonnier, L. Blanc-F'eraud, G. Aubert, and M. Barlaud,
"Deterministic edge-preserving regularization in computed imaging,"
IEEE Transactions on Image Processing, vol. 6, pp. 298-311, 1997.
[10] C. R. Vogel and M. E. Oman, "Fast, robust total variation-based
reconstruction of noisy, blurred images," IEEE Transactions on Image
Processing, vol. 7, pp. 813-824, 1998.
[11] R. H. Chan, C. Ho, and M. Nikolova, "Salt-and-Pepper Noise Removal
by Median-type Noise Detectors and Edge-preserving Regularization,"
IEEE Transactions on Image Processing, vol. 14, pp. 1479-1485, 2005.
[12] Y. Dong and S. Xu. "A New Directional Weighted Median Filter for
Removal of Random-Valued Impulse Noise," IEEE Signal Processing
Letters, vol. 14, no. 3, pp. 193 - 196, 2007.
@article{"International Journal of Electrical, Electronic and Communication Sciences:49287", author = "Zong Chen and Li Zhang", title = "Multi-stage Directional Median Filter", abstract = "Median filter is widely used to remove impulse noise
without blurring sharp edges. However, when noise level increased,
or with thin edges, median filter may work poorly. This paper
proposes a new filter, which will detect edges along four possible
directions, and then replace noise corrupted pixel with estimated
noise-free edge median value. Simulations show that the proposed
multi-stage directional median filter can provide excellent
performance of suppressing impulse noise in all situations.", keywords = "Impulse noise, Median filter, Multi-stage, Edgepreserving", volume = "3", number = "11", pages = "1897-4", }