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Journal Articles Journal of Mathematical Imaging and Vision Year : 2022

Irregularity Index for Vector-Valued Morphological Operators


Mathematical morphology is a valuable theory of nonlinear operators widely used for image processing and analysis. Although initially conceived for binary images, mathematical morphology has been successfully extended to vector-valued images using several approaches. Vector-valued morphological operators based on total orders are particularly promising because they circumvent the problem of false colors. On the downside, they often introduce irregularities in the output image. This paper proposes measuring the irregularity of a vector-valued morphological operator by the relative gap between the generalized sum of pixel-wise distances and the Wasserstein metric. Apart from introducing a measure of the irregularity, referred to as the irregularity index, this paper also addresses its computational implementation. Precisely, we distinguish between the ideal global and the practical local irregularity indexes. The local irregularity index, which can be computed more quickly by aggregating values of local windows, yields a lower bound for the global irregularity index. Computational experiments with natural images illustrate the effectiveness of the proposed irregularity indexes. Keywords mathematical morphology • vector-valued images • total order • irregularity issue • optimal transport.
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hal-03649895 , version 1 (23-04-2022)


  • HAL Id : hal-03649895 , version 1


Marcos Valle, Marco Aurélio Granero, Samuel Francisco, Santiago Velasco-Forero. Irregularity Index for Vector-Valued Morphological Operators. Journal of Mathematical Imaging and Vision, In press. ⟨hal-03649895⟩
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