SAR IMAGE SEGMENTATION VIA NON-LOCAL ACTIVE CONTOURS

被引:7
作者
Liu, Gang [1 ]
Xia, Gui-Song [1 ]
Yang, Wen
Xue, Nan [1 ]
机构
[1] Wuhan Univ, Key State Lab LIESMARS, Wuhan 430079, Peoples R China
来源
2014 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2014年
关键词
SAR image segmentation; non-local processing; active contours; LEVEL-SET;
D O I
10.1109/IGARSS.2014.6947294
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页码:3730 / 3733
页数:4
相关论文
共 13 条
[1]   Multiregion level-set partitioning of synthetic aperture radar images [J].
Ben Ayed, I ;
Mitiche, A ;
Belhadj, Z .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2005, 27 (05) :793-800
[2]   Image Denoising Methods. A New Nonlocal Principle [J].
Buades, A. ;
Coll, B. ;
Morel, J. M. .
SIAM REVIEW, 2010, 52 (01) :113-147
[3]   Iterative Weighted Maximum Likelihood Denoising With Probabilistic Patch-Based Weights [J].
Deledalle, Charles-Alban ;
Denis, Loic ;
Tupin, Florence .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2009, 18 (12) :2661-2672
[4]   Edge location in SAR images:: Performance of the likelihood ratio filter and accuracy improvement with an active contour approach [J].
Germain, O ;
Réfrégier, P .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2001, 10 (01) :72-78
[5]  
Hu L, 2010, LECT NOTES COMPUT SC, V6297, P549
[6]  
Jung MY, 2012, SIAM J IMAGING SCI, V5, P1022, DOI 10.1137/11085863X
[7]   SNAKES - ACTIVE CONTOUR MODELS [J].
KASS, M ;
WITKIN, A ;
TERZOPOULOS, D .
INTERNATIONAL JOURNAL OF COMPUTER VISION, 1987, 1 (04) :321-331
[8]   FRONTS PROPAGATING WITH CURVATURE-DEPENDENT SPEED - ALGORITHMS BASED ON HAMILTON-JACOBI FORMULATIONS [J].
OSHER, S ;
SETHIAN, JA .
JOURNAL OF COMPUTATIONAL PHYSICS, 1988, 79 (01) :12-49
[9]   SAR Image Segmentation Based on Level Set With Stationary Global Minimum [J].
Shuai, Yongmin ;
Sun, Hong ;
Xu, Ge .
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2008, 5 (04) :644-648
[10]  
Soumekh M., 1999, Synthetic Aperture Radar Signal Processing with MATLAB Algorithms