n元数学形态学

Emmanuel Chevallier, Augustin Chevallier, J. Angulo
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引用次数: 7

摘要

摘要二值图像上的数学形态学可以用集合论来充分描述。然而,对于灰度图像,仅用数学形态学来表述是不够的。这种类型的图像需要引入灰度偏阶的概念,以及sup和inf算子的定义。更一般地说,数学形态学现在是在晶格理论的背景下描述的。几十年来,人们主要基于向量顺序的概念,尝试在多变量图像(如彩色图像)上使用数学形态学。然而,这些尝试都没有取得令人完全满意的结果。而不是直接针对多元的情况下,我们首先提出了二值数学形态学的扩展到一个中间情况:图像由有限数量的独立无序标签组成。然后,我们提出了对连续情况的第二次推广。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
N-ary Mathematical Morphology
Abstract Mathematical morphology on binary images can be fully described by set theory. However, it is not sufficient to formulate mathematical morphology for grey scale images. This type of images requires the introduction of the notion of partial order of grey levels, together with the definition of sup and inf operators. More generally, mathematical morphology is now described within the context of the lattice theory. For a few decades, attempts are made to use mathematical morphology on multivariate images, such as color images, mainly based on the notion of vector order. However, none of these attempts has given fully satisfying results. Instead of aiming directly at the multivariate case we propose first an extension of binary mathematical morphology to an intermediary situation: images composed of a finite number of independent unordered labels. We propose then an second extension to a continuous case.
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