article · 2013

Unsupervised structuring element estimation of morphological opening and closing with GA

Yosuke Nabetani, Mitsuji Muneyasu, Akira Asano

Cited by 1Abstract and details only

Abstract

In this paper, we propose an unsupervised design method for optimal structuring element (SE) of morphological filters. We formulate the design of SE as an optimization problem, and estimate an optimal shape and brightness of SE directly from degraded images. We estimated an optimal shape and brightness by using a Genetic Algorithm (GA). Estimation of SE that can remove noise while preserving original signals is achieved by objective function that use Rank-Ordered Logarithmic Differences (ROLD) statistic for the impulse noise detection.

Cite this paper

APA 7

Nabetani, Y., Muneyasu, M., & Asano, A. (2013). Unsupervised structuring element estimation of morphological opening and closing with GA. https://doi.org/10.1109/ispacs.2013.6704564

MLA 9

Nabetani, Yosuke, et al. “Unsupervised structuring element estimation of morphological opening and closing with GA.” vol. 2749, 2013, pp. 297–302, https://doi.org/10.1109/ispacs.2013.6704564.

Chicago

Nabetani, Yosuke, Mitsuji Muneyasu, and Akira Asano. 2013. “Unsupervised structuring element estimation of morphological opening and closing with GA.” https://doi.org/10.1109/ispacs.2013.6704564.

Harvard

Nabetani, Y., Muneyasu, M. and Asano, A. (2013) ‘Unsupervised structuring element estimation of morphological opening and closing with GA’. Available at: https://doi.org/10.1109/ispacs.2013.6704564.

BibTeX

@article{nabetani2013unsupervised,
  title = {{Unsupervised structuring element estimation of morphological opening and closing with GA}},
  author = {Nabetani, Yosuke and Muneyasu, Mitsuji and Asano, Akira},
  volume = {2749},
  pages = {297--302},
  year = {2013},
  doi = {10.1109/ispacs.2013.6704564}
}

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