SAR Image Segmentation via Non-local Active Contours

Gang Liu (1) , Gui-Song Xia (1) , Wen Yang (2)

1 State Key Lab. of Information Engineering in Surveying, Mapping and Remote Sensing
2 DSP - Signal Processing Lab

This paper presents a method for SAR image segmentation by relying on active contour model with the non-local processing principle~\cite{Buades}. The idea is to partition a SAR image via computing the patch similarity in the SAR image non-locally, and formulize the segmentation problem with an active contour model. More precisely, after computing the statistical features of SAR images, non-local comparisons between feature patches are used to calculate the active contour energy, which is defined by integrating the interactions between pairs of patches inside and outside the segmented region. A level set method is finally used to minimize the non-local energy. Compared with existing approaches for SAR image segmentation, the only requirement of this method is a local similarity between patches, and it is less sensitive to initial segmentation. The experimental results show the effectiveness and feasibility of the proposed method.

Mots clés: segmentation; non-local; active contour

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]; Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Gang Liu, Gui-Song Xia, Wen Yang. SAR Image Segmentation via Non-local Active Contours. 2013. ⟨hal-00839601⟩