基于PCDM香农熵的全极化SAR图像船舶目标检测方法
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摘要
极化合成孔径雷达(PolSAR)数据包含了丰富的地物极化散射信息,已被广泛应用于海上交通监测与目标检测。根据船舶目标与海杂波背景在图像上的极化响应差异,提出了一种基于极化协方差差异矩阵PCDM(Polarimetric Covariance Difference Matrix)香农熵的全极化SAR图像船舶目标检测方法。首先计算极化协方差矩阵中元素与邻域元素的差值,由此得到协方差差异矩阵,以提高"船—海"对比度。然后根据香农熵计算公式提取图像的香农熵特征,并依据目标和背景的不同特性对船舶进行检测。针对检测结果中存在的由方位向模糊导致的虚警,根据目标与方位向模糊的偏移量和能量比关系进行移除。利用Radarsat-2全极化精细扫描数据和高分三号GF-3全极化条带1数据进行实验,并将提出的方法与SPAN方法、HV通道、PWF方法进行对比。结果表明:该方法能有效增强船海对比度,并有效提高检测准确率。
Polarimetric Synthetic Aperture Radar(PolSAR)data contains rich polarization information about the scattering properties of ground objects,having been widely used in maritime monitoring and objects detection.The polarization reaction differences between ship targets and sea clutters are analyzed.A ship detection method using the Shannon entropy of the Polarimetric Covariance Difference Matrix(PCDM)is proposed in this paper,which is applied to fully polarimetric SAR images.To enhance the contrast between the ship targets and sea background,the PCDM is generated by calculating the elemental differences between the polarimetric covariance matrix at each pixel and its neighbors.Then the Shannon entropy of SAR images are extracted on the basis of the Shannon entropy calculation formula,and the character difference between the ships and background in the Shannon entropy map is presented for ship detection.The false alarms in the detection result caused by the azimuth ambiguities are removed,based on the displacement distance and energy ratio relationship,between the target and azimuth ambiguity.The Radarsat-2 Fine Quad data and the Chinese GF-3 Quad-Polarimetric Stripmap Ⅰ data are used,to verify the effectiveness of the proposed method,and the SPAN method,HV channel image and polarimetric whitening filter(PWF)method are applied for comparison.The detection and comparison results indicate that the proposed method is able to effectively enhance the ship-sea contrast,and has higher detection accuracy.
Polarimetric Synthetic Aperture Radar(PolSAR)data contains rich polarization information about the scattering properties of ground objects,having been widely used in maritime monitoring and objects detection.The polarization reaction differences between ship targets and sea clutters are analyzed.A ship detection method using the Shannon entropy of the Polarimetric Covariance Difference Matrix(PCDM)is proposed in this paper,which is applied to fully polarimetric SAR images.To enhance the contrast between the ship targets and sea background,the PCDM is generated by calculating the elemental differences between the polarimetric covariance matrix at each pixel and its neighbors.Then the Shannon entropy of SAR images are extracted on the basis of the Shannon entropy calculation formula,and the character difference between the ships and background in the Shannon entropy map is presented for ship detection.The false alarms in the detection result caused by the azimuth ambiguities are removed,based on the displacement distance and energy ratio relationship,between the target and azimuth ambiguity.The Radarsat-2 Fine Quad data and the Chinese GF-3 Quad-Polarimetric Stripmap Ⅰ data are used,to verify the effectiveness of the proposed method,and the SPAN method,HV channel image and polarimetric whitening filter(PWF)method are applied for comparison.The detection and comparison results indicate that the proposed method is able to effectively enhance the ship-sea contrast,and has higher detection accuracy.
引文
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[11]Gao G,Wang X,Niu M.Statistical Modeling of the Reflection Symmetry Metric for Sea Clutter in Dual-Polarimetric SAR Data[J].IEEE Journal of Oceanic Engineering,2016,41(2):339-345.
[12]Marino A,Cloude S R,Woodhouse I H.Detecting Depolarized Targets Using a Bew Geometrical Perturbation Filter[J].IEEE Transactions on Geoscience and Remote Sensing,2012,50(10):3787-3799.
[13]Marino A.A Notch Filter for Ship Detection with Polarimetric SAR Data[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2013,6(3):1219-1232.
[14]Marino A,Hajnsek I.Statistical Tests for a Ship Detector based on the Polarimetric Notch Filter[J].IEEE Transactions on Geoscience and Remote Sensing,2015,53(8):4578-4595.
[15]Réfrégier P,Morio J.Shannon Entropy of Partially Polarized and Partially Coherent Light with Gaussian Fluctuations[J].Journal of the Optical Society of America A,2006,23(12):3036-3044.
[16]Morio J,Refregier P,Goudail F,et al.A Characteriza-tion of Shannon Entropy and Bhattacharyya Measure of Contrast in Polarimetric and Interferometric SAR Image[J].Proceedings of the IEEE,2009,97(6):1097-1108.
[17]Long Mengqi,Yang Xuezhi,Meng Junmin,et al.Dual-polarimetric SAR Data for Ship Detection based on Shannon Entropy[J].Remote Sensing Information,2015,30(5):14-19,25.[龙梦启,杨学志,孟俊敏,等.利用香农熵的双极化合成孔径雷达船只检测[J].遥感信息,2016,41(2):339-345.]
[18]Zhang T,Yang Z,Xiong H.PolSAR Ship Detection based on the Polarimetric Covariance Difference Matrix[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2017,10(7):3348-3359.
[2]Touzi R,Hurley J,Vachon P W.Optimization of the Degree of Polarization for Enhanced Ship Detection Using Polarimetric Radarsat-2[J].IEEE Transactions on Geoscience and Remote Sensing,2015,53(10):5403-5424.
[3]Shirvany R,Chabert M,Tourneret J Y.Ship and Oil-spill Detection Using the Degree of Polarization in Linear and Hybrid/Compact Dual-pol SAR[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2012,5(3):885-892.
[4]Yang J,Zhang H,Yamaguchi Y.GOPCE-based approach to ship detection[J].IEEE Geoscience and Remote Sensing Letters,2012,9(6):1089-1093.
[5]Wang W,Ji Y,Lin X.A Novel Fusion-based Ship Detection Method from Pol-SAR Images[J].Sensors,2015,15(10):25072-25089.
[6]Velotto D,Soccorsi M,Lehner S.Azimuth Ambiguities Removal for Ship Detection Using Full Polarimetric X-band SAR Data[J].IEEE Transactions on Geoscience and Remote Sensing,2014,52(1):76-88.
[7]Nunziata F,Migliaccio M,Brown C E.Reflection Symmetry for Polarimetric Observation of Man-made Metallic Targets at Sea[J].IEEE Journal of Oceanic Engineering,2012,37(3):384-394.
[8]Wu Bingjie,Zhang Bo,Zhang Hong.Ship Detction from Fully Polarimetric SAR Images based on Improved S-NMF Algorithm[J].Remote Sensing Technology and Application,2013,28(2):217-224.[吴冰洁,张波,张红.基于改进的S-NMF方法的全极化SAR船舶检测[J].遥感技术与应用,2013,28(2):217-224.]
[9]Song S,Xu B,Yang J.Ship Detection in Polarimetric SAR Images via Variational Bayesian Inference[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2017,10(6):2819-2829.
[10]Wang C,Wang Z,Zhang H,et al.A PolSAR Ship Detector based on a Multi-polarimetric Feature Combination Using Visual Attention[J].International Journal of Remote Sensing,2014,35(22):7763-7774.
[11]Gao G,Wang X,Niu M.Statistical Modeling of the Reflection Symmetry Metric for Sea Clutter in Dual-Polarimetric SAR Data[J].IEEE Journal of Oceanic Engineering,2016,41(2):339-345.
[12]Marino A,Cloude S R,Woodhouse I H.Detecting Depolarized Targets Using a Bew Geometrical Perturbation Filter[J].IEEE Transactions on Geoscience and Remote Sensing,2012,50(10):3787-3799.
[13]Marino A.A Notch Filter for Ship Detection with Polarimetric SAR Data[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2013,6(3):1219-1232.
[14]Marino A,Hajnsek I.Statistical Tests for a Ship Detector based on the Polarimetric Notch Filter[J].IEEE Transactions on Geoscience and Remote Sensing,2015,53(8):4578-4595.
[15]Réfrégier P,Morio J.Shannon Entropy of Partially Polarized and Partially Coherent Light with Gaussian Fluctuations[J].Journal of the Optical Society of America A,2006,23(12):3036-3044.
[16]Morio J,Refregier P,Goudail F,et al.A Characteriza-tion of Shannon Entropy and Bhattacharyya Measure of Contrast in Polarimetric and Interferometric SAR Image[J].Proceedings of the IEEE,2009,97(6):1097-1108.
[17]Long Mengqi,Yang Xuezhi,Meng Junmin,et al.Dual-polarimetric SAR Data for Ship Detection based on Shannon Entropy[J].Remote Sensing Information,2015,30(5):14-19,25.[龙梦启,杨学志,孟俊敏,等.利用香农熵的双极化合成孔径雷达船只检测[J].遥感信息,2016,41(2):339-345.]
[18]Zhang T,Yang Z,Xiong H.PolSAR Ship Detection based on the Polarimetric Covariance Difference Matrix[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2017,10(7):3348-3359.