Calculus of Variations and Geometric Measure Theory

Y. De Castro - V. Duval - R. Petit

Exact recovery of the support of piecewise constant images via total variation regularization

created by petit on 10 Jul 2023
modified on 29 Jun 2024


Submitted Paper

Inserted: 10 jul 2023
Last Updated: 29 jun 2024

Year: 2023

ArXiv: 2307.03709 PDF


This work is concerned with the recovery of piecewise constant images from noisy linear measurements. We study the noise robustness of a variational reconstruction method, which is based on total (gradient) variation regularization. We show that, if the unknown image is the superposition of a few simple shapes, and if a non-degenerate source condition holds, then, in the low noise regime, the reconstructed images have the same structure: they are the superposition of the same number of shapes, each a smooth deformation of one of the unknown shapes. Moreover, the reconstructed shapes and the associated intensities converge to the unknown ones as the noise goes to zero.