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Two methods for image compression/reconstruction using OWA operators

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Bustince, H. and Paternain, D. and Calvo, T. and De Baets, B. and Fodor, J. and Mesiar, R. and Montero, Javier and Pradera, A. (2011) Two methods for image compression/reconstruction using OWA operators. In Recent Developments in the Ordered Weighted Averaging Operators: Theory and Practice. Studies in Fuzziness and Soft Computing, II (265). Springer Berlin Heidelberg, Berlin, pp. 229-253. ISBN 978-3-642-17909-9

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Official URL: http://link.springer.com/chapter/10.1007%2F978-3-642-17910-5_12


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Abstract

In this chapter we address image compression by means of two alternative algorithms. In the first algorithm, we associate to each image an interval-valued fuzzy relation, and we build an image which is n times smaller than the original one, by using two-dimensional OWA operators. The experimental results show that, in this case, best results are obtained with ME-OWA operators. In the second part of the work, we describe a reduction algorithm that replaces the image by several eigen fuzzy sets associated with it. We obtain these eigen fuzzy sets by means of an equation that relates the OWA operators we use and the relation (image) we consider. Finally, we present a reconstruction method based on an algorithm which minimizes a cost function, with this cost function built by means of two-dimensional OWA operators.


Item Type:Book Section
Subjects:Sciences > Mathematics > Operations research
ID Code:30292
Deposited On:26 May 2015 08:34
Last Modified:22 Apr 2016 13:34

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