基于广义Gamma分布的高分辨率SAR图像海岸线检测
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摘要
本文针对高分辨率SAR图像,采用广义Gamma分布(GΓD)对杂波进行建模,在此基础上提出一种基于水平集分割的海岸线检测方法.GΓD是一种高度灵活的经验分布模型,能够对SAR图像不同类型的地物进行有效建模,其参数可由对数累量法估计得到.基于该分布建立能量泛函,并通过水平集方法最小化能量泛函进行海陆分割,得到海岸线检测结果.利用两幅Terra SAR-X实测SAR图像实验证明,该方法可以实现更精确的海岸线检测.
A new level set method has been proposed for coastline detection in high-resolution SAR images based on the generalized Gamma distribution( GΓD). The GΓD is a statistical model with high flexibility,which is able to characterize the diversity of scenes in SAR images effectively. The parameter estimation of the GΓD is realized by the method of logcumulants.Then the energy functional is formulated based on the GΓD. The coastline detection is achieved by minimizing the proposed energy functional using the level set segmentation method. Experimental results with measured TerraSAR-X images have demonstrated that the proposed method can obtain more precise coastline detection results.
A new level set method has been proposed for coastline detection in high-resolution SAR images based on the generalized Gamma distribution( GΓD). The GΓD is a statistical model with high flexibility,which is able to characterize the diversity of scenes in SAR images effectively. The parameter estimation of the GΓD is realized by the method of logcumulants.Then the energy functional is formulated based on the GΓD. The coastline detection is achieved by minimizing the proposed energy functional using the level set segmentation method. Experimental results with measured TerraSAR-X images have demonstrated that the proposed method can obtain more precise coastline detection results.
引文
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[21]Martin P,Réfrégier P,Goudail F,et al.Influence of the noise model on level set active contour segmentation[J].IEEE Transactions on Pattern Analysis and M achine Intelligence,2004,26(6):799-803.
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[2]Mashaly A S,Abd Elkawy E F,Mahmoud T A.Ship detection in SAR images using efficient land masking methods[A].International Society for Optics and Photonics[C].Baltimore,USA:SPIE Defense Security,2014.90930G-90930G-9.
[3]Niedermeier A,Romaneessen E,Lehner S.Detection of coastlines in SAR images using w avelet methods[J].IEEE Transactions on Geoscience and Remote Sensing,2000,38(5):2270-2281.
[4]毛成林,万寿红,岳丽华,等.一种基于双树复小波变换的SAR图像边缘检测算法[J].中国科学院大学学报,2014,31(2):238-242,248.M ao C L,Wan S H,Yue L H,et al.An edge detection algorithm of SAR images based on dual-tree complex w avelet transform[J].Journal of University of Chinese Academy of Sciences,2014,31(2):238-242,248.(in Chinese)
[5]Silveira M,Heleno S.Separation between water and land in SAR images using region-based level sets[J].IEEE Geoscience and Remote Sensing Letters,2009,6(3):471-475.
[6]黄魁华,张军.局部统计活动轮廓模型的SAR图像海岸线检测[J].遥感学报,2011,15(4):737-749.Huang K H,Zhang J.A coastline detection method using SAR images based on the local statistical active contour model[J].Journal of Remote Sensing,2011,15(4):737-749.(in Chinese)
[7]Ding X,Nunziata F,Li X,et al.Performance analysis and validation of w aterline extraction approaches using singleand dual-polarimetric SAR data[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2015,8(3):1019-1027.
[8]Liu Z,Li F,Li N,et al.A novel region-merging approach for coastline extraction from sentinel-1A IW mode SAR imagery[J].IEEE Geoscience and Remote Sensing Letters,2016,13(3):324-328.
[9]Yang X,Gao X,Tao D,et al.An efficient MRF embedded level set method for image segmentation[J].IEEE Transactions on Image Processing,2015,24(1):9-21.
[10]Ayed I B,Mitiche A,Belhadj Z.Multiregion level-set partitioning of synthetic aperture radar images[J].IEEE Transactions on Pattern Analysis and M achine Intelligence,2005,27(5):793-800.
[11]Marques R C P,Medeiros F N,Nobre J S.SAR image segmentation based on level set approach and G0Amodel[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2012,34(10):2046-2057.
[12]Oliver C J.A model for non-Rayleigh scattering statistics[J].Journal of Modern Optics,1984,31(6):701-722.
[13]Frery A C,Muller H J,Yanasse C C F,et al.A model for extremely heterogeneous clutter[J].IEEE Transactions on Geoscience and Remote Sensing,1997,35(3):648-659.
[14]Delignon Y,Garello R,Hillion A.Statistical modelling of ocean SAR images[J].IEE Proceedings-Radar,Sonar and Navigation,1997,144(6):348-354.
[15]Oliver C J.Optimum texture estimators for SAR clutter[J].Journal of Physics D:Applied Physics,1993,26(11):1824.
[16]Tison C,Nicolas J M,Tupin F,et al.A new statistical model for M arkovian classification of urban areas in highresolution SAR images[J].IEEE Transactions on Geoscience and Remote Sensing,2004,42(10):2046-2057.
[17]Li H C,Hong W,Wu Y R,et al.On the empirical-statistical modeling of SAR images w ith generalized Gamma distribution[J].IEEE Journal of Selected Topics in Signal Processing,2011,5(3):386-397.
[18]Qin X,Zou H,Zhou S,et al.Region-based classification of SAR images using Kullback-Leibler distance betw een generalized gamma distributions[J].IEEE Geoscience and Remote Sensing Letters,2015,12(8):1655-1659.
[19]Cui S,Schwarz G,Datcu M.A comparative study of statistical models for multilook SAR images[J].IEEE Geoscience and Remote Sensing Letters,2014,11(10):1752-1756.
[20]Krylov V A,Moser G,Serpico S B,et al.On the method of logarithmic cumulants for parametric probability density function estimation[J].IEEE Transactions on Image Processing,2013,22(10):3791-3806.
[21]Martin P,Réfrégier P,Goudail F,et al.Influence of the noise model on level set active contour segmentation[J].IEEE Transactions on Pattern Analysis and M achine Intelligence,2004,26(6):799-803.
[22]Abdou I E,Pratt W K.Quantitative design and evaluation of enhancement/thresholding edge detectors[J].Proceedings of the IEEE,1979,67(5):753-763.
[23]Vese L A,Chan T F.A multiphase level set framework for image segmentation using the M umford and Shah model[J].International Journal of Computer Vision,2002,50(3):271-293.