Title :
SAR image segmentation via non-local active contours
Author :
Gang Liu ; Gui-Song Xia ; Wen Yang ; Nan Xue
Author_Institution :
Key State Lab. LIESMARS, Wuhan Univ., Wuhan, China
Abstract :
This paper presents a method for SAR image segmentation by relying on active contour model with the non-local processing principle [1]. 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.
Keywords :
geophysical image processing; geophysical techniques; image segmentation; minimisation; radar imaging; remote sensing by radar; statistical analysis; synthetic aperture radar; SAR image partitioning; SAR image segmentation; active contour energy; active contour model; feature patch nonlocal comparisons; level set method; nonlocal active contours; nonlocal energy minimization; nonlocal processing; patch similarity; statistical features; Active contours; Computational modeling; Educational institutions; Image edge detection; Image segmentation; Level set; Synthetic aperture radar; SAR image segmentation; active contours; non-local processing;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
DOI :
10.1109/IGARSS.2014.6947294