The effect of discretization on the mean geometry of a 2D random field
Annales Henri Lebesgue, Volume 4 (2021), pp. 1295-1345.

KeywordsPerimeter, Total curvature, Euler Characteristic, excursion sets, discrete geometry, stationary random field, image analysis, Gaussian random field

### Abstract

The study of the geometry of excursion sets of 2D random fields is a question of interest from both the theoretical and the applied viewpoints. In this paper we are interested in the relationship between the perimeter (resp. the total curvature, related to the Euler characteristic by Gauss–Bonnet Theorem) of the excursion sets of a function and the ones of its discretization. Our approach is a weak framework in which we consider the functions that map the level of the excursion set to the perimeter (resp. the total curvature) of the excursion set. We will be also interested in a stochastic framework in which the sets are the excursion sets of 2D random fields. We show in particular that, under some stationarity and isotropy conditions on the random field, in expectation, the perimeter is always biased (with a $4/\pi$ factor), whereas the total curvature is not. We illustrate all our results on different examples of random fields.

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