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On the Use of Lattice OWA Operators in Image Reduction and the Importance of the Orness Measure

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Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2016)

Abstract

In this work we investigate the use of OWA operators in color image reduction. Since the RGB color scheme can be seen as a Cartesian product of lattices, we use the generalization of OWA operators to any complete lattice. However, the behavior of lattice OWA operators in image processing is not easy to predict. Therefore, we propose an orness measure that generalizes the orness measure given by Yager for usual OWA operators. With the aid of this new measure, we are able to classify each OWA operator and to analyze how its properties affect the results of applying OWA operators in an algorithm for reducing color images.

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Acknowledgments

D. Paternain and H. Bustince have been partially supported by Spanish project TIN2013-40765-P. R. Mesiar has been partially supported by grant APVV-14-0013.

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Correspondence to Daniel Paternain .

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Paternain, D., Ochoa, G., Lizasoain, I., Barrenechea, E., Bustince, H., Mesiar, R. (2016). On the Use of Lattice OWA Operators in Image Reduction and the Importance of the Orness Measure. In: Carvalho, J., Lesot, MJ., Kaymak, U., Vieira, S., Bouchon-Meunier, B., Yager, R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2016. Communications in Computer and Information Science, vol 610. Springer, Cham. https://doi.org/10.1007/978-3-319-40596-4_52

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  • DOI: https://doi.org/10.1007/978-3-319-40596-4_52

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40595-7

  • Online ISBN: 978-3-319-40596-4

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