基于差异度迭代的极化SAR图像机场跑道检测算法
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摘要
机场在军事和交通运输领域都有很重要的作用,对它的自动检测具有重大意义。本文提出了一种利用极化SAR(Polarimetric Synthetic Aperture Radar)图像检测机场跑道的方法。首先,利用SLIC(Simple linear Iterative Clustering)算法对极化SAR图像进行超像素分割;然后利用新三分量分解和极化散射熵对图像进行粗分类,再利用改进的K均值聚类结合差异度迭代的方法完成精细分类,最后利用跑道的散射特性和几何结构特征从分类结果中提取完整的机场区域。本文采用极化SAR数据进行实验检测,结果表明该方法能有效的检测出机场跑道,并且保持结构完整,边缘细节清晰,虚警率低。
Airports are crucial infrastructures in both civil and military transportation systems. Automatic detection of airports then has been attracting significant research interests in the remote sensing areas. A method for detecting airport runways in a Polarimetric Synthetic Aperture Radar(PolSAR) image using difference degree iteration is proposed in this paper. Superpixels are generated by Simple Linear Iterative Clustering(SLIC) algorithm which is applied to the PolSAR image in the segmentation step, followed by a coarse classification according to the three-component decomposition feature and scattering entropy. The fine classification, combining the enhanced K-means clustering method with the difference degree iteration, is then applied. The extraction of runways and the complete airport areas from the classification results can then be achieved by exploiting both of the scattering and geometric features. The UAVSAR data set is used for verifying the performance of the proposed method. And the results suggest that the airport runway can be detected effectively by the proposed method, while maintaining the detailed structures intact with clear edges. A low false alarm rate is also exhibited during the numerical experiments.
Airports are crucial infrastructures in both civil and military transportation systems. Automatic detection of airports then has been attracting significant research interests in the remote sensing areas. A method for detecting airport runways in a Polarimetric Synthetic Aperture Radar(PolSAR) image using difference degree iteration is proposed in this paper. Superpixels are generated by Simple Linear Iterative Clustering(SLIC) algorithm which is applied to the PolSAR image in the segmentation step, followed by a coarse classification according to the three-component decomposition feature and scattering entropy. The fine classification, combining the enhanced K-means clustering method with the difference degree iteration, is then applied. The extraction of runways and the complete airport areas from the classification results can then be achieved by exploiting both of the scattering and geometric features. The UAVSAR data set is used for verifying the performance of the proposed method. And the results suggest that the airport runway can be detected effectively by the proposed method, while maintaining the detailed structures intact with clear edges. A low false alarm rate is also exhibited during the numerical experiments.
引文
[1] 周晓光,匡纲要,万建伟.极化SAR图像分类综述[J].信号处理,2008(5):806- 812.Zhou X G,Kuang G Y,Wan J W.A Review of Polarimetric SAR Image Classification[J].Signal Processing,2008(5):806- 812.(in Chinese)
[2] Aytekin O,Zongur U,Halici U.Texture-based airport runway detection[J].IEEE Geoscience and Remote Sensing Letters,2013,10(3):471- 475.
[3] Gupta P,Agrawal A.Airport detection in high-resolution panchromatic satellite images[J].J Inst Eng(India),2007,88(5):3-9.
[4] Xiong W,Zhong J,Zhou Y.Automatic recognition of airfield runways based on Radon transform and hypothesis testing in SAR images[C]//Millimeter Waves,2012:462- 465.
[5] ümit Budak,Hal?c? U,?engür A,et al.Efficient Airport Detection Using Line Segment Detector and Fisher Vector Representation[J].IEEE Geoscience & Remote Sensing Letters,2016,13(8):1079-1083.
[6] 晋瑞锦,周伟,杨健.大场景下的极化SAR机场检测[J].清华大学学报:自然科学版,2014(12):1588-1593.Jin R J,Zhou W,Yang J.Airport automatic detection in large-scale polarimetric SAR images[J].J Tsinghua Univ:Sci&Technol,2014(12):1588-1593.(in Chinese)
[7] Han P,Cheng Z,Chang L.Automatic Runway Detection Based On Unsupervised Classification In PolSAR Image[C]//2016 Integrated Communications Navigation and Surveillance(ICNS),2016:6E3-1- 6E3- 8.
[8] 韩萍,徐建飒.复杂场景下的极化SAR图像机场跑道检测[J].信号处理,2013,29(9):1220-1226.Han P,Xu J S.Runways Detection in ComPlex Scenes of Polarimetric Synthetic Aperture Radar Image[J].Journal of Signal Processing,2013,29(9):1220-1226.(in Chinese)
[9] 韩萍,季静敏,石庆研.散射模型与Wishart分类相结合的极化SAR图像分类[J].信号处理,2015,31(11):1497-1503.Han P,Ji J M,Shi Q Y.Classification of Polarimetric SAR Images With Scattering Model and Wishart Classifier[J].Journal of Signal Processing,2015,31(11):1497-1503.(in Chinese)
[10] Freeman A,Durden S L.A three-component scattering model to describe polarimetric SAR data[J].IEEE Transactions on Geoscience and Remote Sensing,1998,36(3):963-973.
[11] An W T,Cui Y,Yang J.Three-component model-based decomposition for polarimetric SAR data[J].IEEE Transactions on Geoscience and Remote Sensing,2010,48(6):2732-2739.
[12] 安文韬.基于极化SAR的目标极化分解与散射特征提取研究[D].[博士学位论文].北京:清华大学,2010.An W T.Dissertation The Polarimetric Decomposition and Scattering Characteristic Extraction of Polarimetric SAR[D].[the degree of Doctor].Beijing:Tsinghua University,2010.(in Chinese)
[13] 舒浩浩,陈盛双,李石君.基于最优K均值的时空动态背景模型[J].小型微型计算机系统,2019,40(2):413- 419.Shu H H,Chen S S,Li S J,Spatiotemporal Dynamic Background Model Based on Optimal K-means Clustering[J].Journal of Chinese Computer Systems,2019,40(2):413- 419.(in Chinese)
[14] Achanta R,Shaji A,Smith K,et al.SLIC superpixels compared to state-of-the-art superpixel methods[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2012,34(11):2274-2282.
[15] 韩萍,常玲,程争,等.基于h/q分解和贝叶斯迭代分类的跑道检测算法[J].系统工程与电子技术,2016,38(9):2048-2054.Han P,Chang L,Cheng Z,et al.Runways detection based on h/q decomposition and iterative Bayesian classification[J].Systems Engineering and Electronics,2016,38(9):2048-2054.(in Chinese)
[16] Kou Z,Shi Z,Liu L.Airport Detection Based on Line Segment Detector[C]//International Conference on Computer Vision in Remote Sensing,2013:72-77.
[17] Maurya H,Chauhan A,Panigrahi R K.A fast alternative to three-and four-component scattering models for polarimetric SAR image decomposition[J].Remote Sensing Letters,2017,8(8):781-790.
[18] 邢相薇,计科峰,孙即祥.基于目标分解和加权SVM分类的极化SAR图像舰船检测[J].信号处理,2011,27(9):1440-1445.Xing X W,Ji K F,Sun J X.Ship Detection in Polarimetric SAR lmagery Based on Target Decomposition and Weighted SVM Classifier[J].Signal Processing,2011,27(9):1440-1445.(in Chinese)
[19] Liu N,Cui Z,Cao Z,et al.Airport Detection in Large-Scale SAR Images via Line Segment Grouping and Saliency Analysis[J].IEEE Geoscience & Remote Sensing Letters,2018,15(3):434- 438.
[20] Lv W,Dai K,Wu L,et al.Runway Detection in SAR Images Based on Fusion Sparse Representation and Semantic Spatial Matching[J].IEEE Access,2018:1-9.
[21] Lee J S,Pottier E.Polarimetric Radar Imaging:From Basics to Applications[M].Florida:CRC Press,2009:60-153.
[22] Jiao L,Liu F.Wishart Deep Stacking Network for Fast POLSAR Image Classification[J].IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society,2016,25(7):3273-3286.
[23] 韩萍,徐建飒,赵爱军.基于多级分类的 PolSAR 图像机场跑道检测[J].系统工程与电子技术,2014(5):866- 871.Han P,Xu J S,Zhao A J.PolSAR image runways detection based on multi-stage classification[J].Systems Engineering and Electronics,2014(5):866- 871.(in Chinese)
[24] Yamaguchi Y,Moriyama T,Ishido M,et al.Four-component scattering model for polarimetric SAR image decomposition[J].IEEE Transactions on Geoscience and Remote Sensing,2005,43(8):1699-1706.
[2] Aytekin O,Zongur U,Halici U.Texture-based airport runway detection[J].IEEE Geoscience and Remote Sensing Letters,2013,10(3):471- 475.
[3] Gupta P,Agrawal A.Airport detection in high-resolution panchromatic satellite images[J].J Inst Eng(India),2007,88(5):3-9.
[4] Xiong W,Zhong J,Zhou Y.Automatic recognition of airfield runways based on Radon transform and hypothesis testing in SAR images[C]//Millimeter Waves,2012:462- 465.
[5] ümit Budak,Hal?c? U,?engür A,et al.Efficient Airport Detection Using Line Segment Detector and Fisher Vector Representation[J].IEEE Geoscience & Remote Sensing Letters,2016,13(8):1079-1083.
[6] 晋瑞锦,周伟,杨健.大场景下的极化SAR机场检测[J].清华大学学报:自然科学版,2014(12):1588-1593.Jin R J,Zhou W,Yang J.Airport automatic detection in large-scale polarimetric SAR images[J].J Tsinghua Univ:Sci&Technol,2014(12):1588-1593.(in Chinese)
[7] Han P,Cheng Z,Chang L.Automatic Runway Detection Based On Unsupervised Classification In PolSAR Image[C]//2016 Integrated Communications Navigation and Surveillance(ICNS),2016:6E3-1- 6E3- 8.
[8] 韩萍,徐建飒.复杂场景下的极化SAR图像机场跑道检测[J].信号处理,2013,29(9):1220-1226.Han P,Xu J S.Runways Detection in ComPlex Scenes of Polarimetric Synthetic Aperture Radar Image[J].Journal of Signal Processing,2013,29(9):1220-1226.(in Chinese)
[9] 韩萍,季静敏,石庆研.散射模型与Wishart分类相结合的极化SAR图像分类[J].信号处理,2015,31(11):1497-1503.Han P,Ji J M,Shi Q Y.Classification of Polarimetric SAR Images With Scattering Model and Wishart Classifier[J].Journal of Signal Processing,2015,31(11):1497-1503.(in Chinese)
[10] Freeman A,Durden S L.A three-component scattering model to describe polarimetric SAR data[J].IEEE Transactions on Geoscience and Remote Sensing,1998,36(3):963-973.
[11] An W T,Cui Y,Yang J.Three-component model-based decomposition for polarimetric SAR data[J].IEEE Transactions on Geoscience and Remote Sensing,2010,48(6):2732-2739.
[12] 安文韬.基于极化SAR的目标极化分解与散射特征提取研究[D].[博士学位论文].北京:清华大学,2010.An W T.Dissertation The Polarimetric Decomposition and Scattering Characteristic Extraction of Polarimetric SAR[D].[the degree of Doctor].Beijing:Tsinghua University,2010.(in Chinese)
[13] 舒浩浩,陈盛双,李石君.基于最优K均值的时空动态背景模型[J].小型微型计算机系统,2019,40(2):413- 419.Shu H H,Chen S S,Li S J,Spatiotemporal Dynamic Background Model Based on Optimal K-means Clustering[J].Journal of Chinese Computer Systems,2019,40(2):413- 419.(in Chinese)
[14] Achanta R,Shaji A,Smith K,et al.SLIC superpixels compared to state-of-the-art superpixel methods[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2012,34(11):2274-2282.
[15] 韩萍,常玲,程争,等.基于h/q分解和贝叶斯迭代分类的跑道检测算法[J].系统工程与电子技术,2016,38(9):2048-2054.Han P,Chang L,Cheng Z,et al.Runways detection based on h/q decomposition and iterative Bayesian classification[J].Systems Engineering and Electronics,2016,38(9):2048-2054.(in Chinese)
[16] Kou Z,Shi Z,Liu L.Airport Detection Based on Line Segment Detector[C]//International Conference on Computer Vision in Remote Sensing,2013:72-77.
[17] Maurya H,Chauhan A,Panigrahi R K.A fast alternative to three-and four-component scattering models for polarimetric SAR image decomposition[J].Remote Sensing Letters,2017,8(8):781-790.
[18] 邢相薇,计科峰,孙即祥.基于目标分解和加权SVM分类的极化SAR图像舰船检测[J].信号处理,2011,27(9):1440-1445.Xing X W,Ji K F,Sun J X.Ship Detection in Polarimetric SAR lmagery Based on Target Decomposition and Weighted SVM Classifier[J].Signal Processing,2011,27(9):1440-1445.(in Chinese)
[19] Liu N,Cui Z,Cao Z,et al.Airport Detection in Large-Scale SAR Images via Line Segment Grouping and Saliency Analysis[J].IEEE Geoscience & Remote Sensing Letters,2018,15(3):434- 438.
[20] Lv W,Dai K,Wu L,et al.Runway Detection in SAR Images Based on Fusion Sparse Representation and Semantic Spatial Matching[J].IEEE Access,2018:1-9.
[21] Lee J S,Pottier E.Polarimetric Radar Imaging:From Basics to Applications[M].Florida:CRC Press,2009:60-153.
[22] Jiao L,Liu F.Wishart Deep Stacking Network for Fast POLSAR Image Classification[J].IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society,2016,25(7):3273-3286.
[23] 韩萍,徐建飒,赵爱军.基于多级分类的 PolSAR 图像机场跑道检测[J].系统工程与电子技术,2014(5):866- 871.Han P,Xu J S,Zhao A J.PolSAR image runways detection based on multi-stage classification[J].Systems Engineering and Electronics,2014(5):866- 871.(in Chinese)
[24] Yamaguchi Y,Moriyama T,Ishido M,et al.Four-component scattering model for polarimetric SAR image decomposition[J].IEEE Transactions on Geoscience and Remote Sensing,2005,43(8):1699-1706.
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