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Existence of Minimizers for the Gaussian Mumford-Shah Model via Covariance Floors on the Value Distribution

Faian Conrad · 2026 · arXiv

DOI: 10.48550/arXiv.2610.29949 · open-access PDF

Arabic

ويستخدم نموذج مومفورد-شاخ غازاني صورة في المناطق من خلال تقليل نسبية غازية منخفضة من المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفاجآت المفا

Machine translation (Meta M2M100); the English original follows.

Abstract

The Gaussian Mumford-Shah model segments an image into regions by minimizing a continuous multivariate Gaussian negative log-likelihood term plus a perimeter penalty. It is used for scalar- and vector-valued images, in particular hyperspectral images, but the existence of a minimizer in general is not guaranteed. The energy is unbounded below whenever the covariance of a single region degenerates, regardless of the perimeter of the regions. A quantitative covariance floor on the covariances of all regions, or equivalently uniform Hölder continuity with exponent at most one of all one-dimension

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