SAR Image Segmentation via Non-local Active Contours

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.

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Additional Info

Field Value
Source https://hal.science/hal-00839601
Author Liu, Gang, Xia, Gui-Song, Yang, Wen
Maintainer CCSD
Last Updated May 7, 2026, 13:02 (UTC)
Created May 7, 2026, 13:02 (UTC)
Identifier hal-00839601
Language en
Rights https://about.hal.science/hal-authorisation-v1/
contributor State Key Lab. of Information Engineering in Surveying, Mapping and Remote Sensing ; Wuhan University [China]
creator Liu, Gang
date 2013-05-01T00:00:00
harvest_object_id fc4e6363-6911-4154-a02a-ff6693db3ebe
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2016-09-16T00:00:00
set_spec type:REPORT