A line segment detector for SAR images with controlled false alarm rate

Chenguang Liu (1) , Rémy Abergel (2, 3, 4) , Yann Gousseau (3, 4) , Florence Tupin (3, 4)

1 LTCI - Laboratoire Traitement et Communication de l'Information
2 MAP5 - UMR 8145 - Mathématiques Appliquées Paris 5
3 IMAGES - Image, Modélisation, Analyse, GEométrie, Synthèse
4 IDS - Département Images, Données, Signal

In this paper we propose to adapt LSD [1] (a state-of-the-art line segment detector for optical images) to SAR images. The first modification is replacing the gradient computation with an exponentially weighted ratio-based method which has a constant false alarm rate for SAR images. Next, we observe that the strong noise removal necessary for processing SAR images strongly impairs the independent hypothesis of the a contrario model used by LSD. A first order Markov chain is used to take the spatial dependencies into consideration. Experiments show that the proposed method has good perfor- mances and the number of false detections is well controlled.

Keywords: a contrario model; first order Markov chain; ratio-based; LSD

Domains: Image Processing [eess.IV]

Chenguang Liu, Rémy Abergel, Yann Gousseau, Florence Tupin. A line segment detector for SAR images with controlled false alarm rate. IGARSS, Jul 2018, Valencia, Spain. ⟨hal-01860265⟩