Redundancy in Gaussian random fields - Archive ouverte HAL Access content directly
Journal Articles ESAIM: Probability and Statistics Year : 2020

Redundancy in Gaussian random fields

Abstract

In this paper, we introduce a notion of spatial redundancy in Gaussian random fields. This study is motivated by applications of the a contrario method in image processing. We define similarity functions on local windows in random fields over discrete or continuous domains. We derive explicit Gaussian asymptotics for the distribution of similarity functions when computed on Gaussian random fields. Moreover, for the special case of the squared L2 norm, we give non-asymptotic expressions in both discrete and continuous periodic settings. Finally, we present fast and accurate approximations of these non-asymptotic expressions using moment methods and matrix projections.
Fichier principal
Vignette du fichier
ps180113.pdf (1.81 Mo) Télécharger le fichier
Origin : Publication funded by an institution
Loading...

Dates and versions

hal-02989001 , version 1 (05-11-2020)

Identifiers

Cite

Valentin de Bortoli, Agnès Desolneux, Bruno Galerne, Arthur Leclaire. Redundancy in Gaussian random fields. ESAIM: Probability and Statistics, 2020, 24, pp.627-660. ⟨10.1051/ps/2020010⟩. ⟨hal-02989001⟩
59 View
53 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More