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Use of idempotent functions in the aggregation of different filters for noise removal

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Abstract
The majority of existing denoising algorithms obtain good results for a specific noise model, and when it is known previously. Nonetheless, there is a lack in denoising algorithms that can deal with any unknown noisy images. Therefore, in this paper, we study the use of aggregation functions for denoising purposes, where the noise model is not necessary known in advance; and how these functions affect the visual and quantitative results of the resultant images.
Keywords
Idempotent function, Denoising, Aggregation function, OWA operator

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MLA
González Jaime, Luis Antonio, et al. “Use of Idempotent Functions in the Aggregation of Different Filters for Noise Removal.” Advances in Intelligent Systems and Computing, edited by Fuchun Sun et al., vol. 214, Springer, 2014, pp. 495–507, doi:10.1007/978-3-642-37832-4_45.
APA
González Jaime, L. A., Nachtegael, M., Kerre, E., & Bustince, H. (2014). Use of idempotent functions in the aggregation of different filters for noise removal. In F. Sun, T. Li, & H. Li (Eds.), Advances in Intelligent Systems and Computing (Vol. 214, pp. 495–507). https://doi.org/10.1007/978-3-642-37832-4_45
Chicago author-date
González Jaime, Luis Antonio, Mike Nachtegael, Etienne Kerre, and Humberto Bustince. 2014. “Use of Idempotent Functions in the Aggregation of Different Filters for Noise Removal.” In Advances in Intelligent Systems and Computing, edited by Fuchun Sun, Tianrui Li, and Hongbo Li, 214:495–507. Berlin, Germany: Springer. https://doi.org/10.1007/978-3-642-37832-4_45.
Chicago author-date (all authors)
González Jaime, Luis Antonio, Mike Nachtegael, Etienne Kerre, and Humberto Bustince. 2014. “Use of Idempotent Functions in the Aggregation of Different Filters for Noise Removal.” In Advances in Intelligent Systems and Computing, ed by. Fuchun Sun, Tianrui Li, and Hongbo Li, 214:495–507. Berlin, Germany: Springer. doi:10.1007/978-3-642-37832-4_45.
Vancouver
1.
González Jaime LA, Nachtegael M, Kerre E, Bustince H. Use of idempotent functions in the aggregation of different filters for noise removal. In: Sun F, Li T, Li H, editors. Advances in Intelligent Systems and Computing. Berlin, Germany: Springer; 2014. p. 495–507.
IEEE
[1]
L. A. González Jaime, M. Nachtegael, E. Kerre, and H. Bustince, “Use of idempotent functions in the aggregation of different filters for noise removal,” in Advances in Intelligent Systems and Computing, Beijing, PR China, 2014, vol. 214, pp. 495–507.
@inproceedings{8086266,
  abstract     = {{The majority of existing denoising algorithms obtain good results for a specific noise model, and when it is known previously. Nonetheless, there is a lack in denoising algorithms that can deal with any unknown noisy images. Therefore, in this paper, we study the use of aggregation functions for denoising purposes, where the noise model is not necessary known in advance; and how these functions affect the visual and quantitative results of the resultant images.}},
  author       = {{González Jaime, Luis Antonio and Nachtegael, Mike and Kerre, Etienne and Bustince, Humberto}},
  booktitle    = {{Advances in Intelligent Systems and Computing}},
  editor       = {{Sun, Fuchun and Li, Tianrui and Li, Hongbo}},
  isbn         = {{9783642378324}},
  issn         = {{2194-5357}},
  keywords     = {{Idempotent function,Denoising,Aggregation function,OWA operator}},
  language     = {{eng}},
  location     = {{Beijing, PR China}},
  pages        = {{495--507}},
  publisher    = {{Springer}},
  title        = {{Use of idempotent functions in the aggregation of different filters for noise removal}},
  url          = {{http://doi.org/10.1007/978-3-642-37832-4_45}},
  volume       = {{214}},
  year         = {{2014}},
}

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