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Generalizing an interval-valued image magnification algorithm using homogeneity measures and interval fusion functions

机译:使用均匀性测度和区间融合函数推广区间值图像放大算法

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In this work we study and generalize an image magnification algorithm based on the use of interval-valued fuzzy sets. The first proposed generalization incorporates an homogeneity measure that allows to model the length of the intervals generated by the algorithm. The second one makes use of several homogeneity measures and, by means of a fusion function, it combines the intervals generated by each individual homogeneity measure. The results show that our generalization outperforms the original algorithm when an appropriate homogeneity measure is used. Moreover, experiments have demonstrated that the second generalization, based on interval fusion functions, avoids low quality results due to bad homogeneity measures.
机译:在这项工作中,我们研究和推广了基于区间值模糊集的图像放大算法。首先提出的一般化方法引入了同质性度量,该度量允许对算法生成的间隔的长度进行建模。第二种方法利用了几种同质性度量,并通过融合函数将每个单独的同质性度量生成的间隔合并在一起。结果表明,当使用适当的同质性度量时,我们的概括优于原始算法。而且,实验表明,基于区间融合函数的第二种概括避免了由于不良同质性度量而导致的低质量结果。

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