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A fuzzy impulse noise detection and reduction method

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Abstract
Removing or reducing impulse noise is a very active research area in image processing. In this paper we describe a new algorithm that is especially developed for reducing all kinds of impulse noise: fuzzy impulse noise detection and reduction method (FIDRM). It can also be applied to images having a mixture of impulse noise and other types of noise. The result is an image quasi without (or with very little) impulse noise so that other filters can be used afterwards. This nonlinear filtering technique contains two separated steps: an impulse noise detection step and a reduction step that preserves edge sharpness. Based on the concept of fuzzy gradient values, our detection method constructs a fuzzy set impulse noise. This fuzzy set is represented by a membership function that will be used by the filtering method, which is a fuzzy averaging of neighboring pixels. Experimental results show that FIDRM provides a significant improvement on other existing filters. FIDRM is not only very fast, but also very effective for reducing little as well as very high impulse noise.
Keywords
image processing, fuzzy filter, impulse noise, membership functions, noise reduction, MEDIAN FILTER, IMAGES

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Chicago
Schulte, Stefan, Mike Nachtegael, Valerie De Witte, Dietrich Van der Weken, and Etienne Kerre. 2006. “A Fuzzy Impulse Noise Detection and Reduction Method.” Ieee Transactions on Image Processing 15 (5): 1153–1162.
APA
Schulte, Stefan, Nachtegael, M., De Witte, V., Van der Weken, D., & Kerre, E. (2006). A fuzzy impulse noise detection and reduction method. IEEE TRANSACTIONS ON IMAGE PROCESSING, 15(5), 1153–1162.
Vancouver
1.
Schulte S, Nachtegael M, De Witte V, Van der Weken D, Kerre E. A fuzzy impulse noise detection and reduction method. IEEE TRANSACTIONS ON IMAGE PROCESSING. 2006;15(5):1153–62.
MLA
Schulte, Stefan, Mike Nachtegael, Valerie De Witte, et al. “A Fuzzy Impulse Noise Detection and Reduction Method.” IEEE TRANSACTIONS ON IMAGE PROCESSING 15.5 (2006): 1153–1162. Print.
@article{335322,
  abstract     = {Removing or reducing impulse noise is a very active research area in image processing. In this paper we describe a new algorithm that is especially developed for reducing all kinds of impulse noise: fuzzy impulse noise detection and reduction method (FIDRM). It can also be applied to images having a mixture of impulse noise and other types of noise. The result is an image quasi without (or with very little) impulse noise so that other filters can be used afterwards. This nonlinear filtering technique contains two separated steps: an impulse noise detection step and a reduction step that preserves edge sharpness. Based on the concept of fuzzy gradient values, our detection method constructs a fuzzy set impulse noise. This fuzzy set is represented by a membership function that will be used by the filtering method, which is a fuzzy averaging of neighboring pixels. Experimental results show that FIDRM provides a significant improvement on other existing filters. FIDRM is not only very fast, but also very effective for reducing little as well as very high impulse noise.},
  author       = {Schulte, Stefan and Nachtegael, Mike and De Witte, Valerie and Van der Weken, Dietrich and Kerre, Etienne},
  issn         = {1057-7149},
  journal      = {IEEE TRANSACTIONS ON IMAGE PROCESSING},
  keyword      = {image processing,fuzzy filter,impulse noise,membership functions,noise reduction,MEDIAN FILTER,IMAGES},
  language     = {eng},
  number       = {5},
  pages        = {1153--1162},
  title        = {A fuzzy impulse noise detection and reduction method},
  url          = {http://dx.doi.org/10.1109/TIP.2005.864179},
  volume       = {15},
  year         = {2006},
}

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