A convex approach to super-resolution and regularization of lines in images

Kévin Polisano (1) , Marianne Clausel (2) , Valérie Perrier (1) , Laurent Condat (3)

1 CVGI - Calcul des Variations, Géométrie, Image
2 IECL - Institut Élie Cartan de Lorraine
3 GIPSA-SIGMAPHY - GIPSA - Signal Images Physique

We present a new convex formulation for the problem of recovering lines in degraded images. Following the recent paradigm of super-resolution, we formulate a dedicated atomic norm penalty and solve this optimization problem by a primal-dual algorithm. Then, a spectral estimation method recovers the line parameters, with subpixel accuracy.

Domains: Classical Analysis and ODEs [math.CA]

Kévin Polisano, Marianne Clausel, Valérie Perrier, Laurent Condat. A convex approach to super-resolution and regularization of lines in images. Curves & Surfaces, Jun 2018, Arcachon, France. ⟨hal-03420326⟩