收稿：2017-06-30，
录用：2017-11-21，
纸质出版：2019-03
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为有效利用简缩极化SAR进行海洋溢油检测，本文基于简缩极化特征值分析，提出了3个用于简缩极化溢油检测的参数，引入了基于简缩极化特征值分解的简缩极化熵Hc(Compact Polarization Entropy)、简缩极化比参数PFc(Compact Polarization Fraction)、简缩极化基准高度PHc(Compact Polarization Pedestal Height)特征进行海洋溢油检测。海表的散射类型主要为低熵散射(小粗糙面发生的Bragg散射)，为弱去极化、弱散射过程随机性状态，由于溢油会阻尼海水的Bragg散射，使其熵值变高、呈去极化、强散射过程随机性状态，故简缩极化熵、简缩极化比参数和简缩极化基准高度可以用来检测海洋溢油。本文采用C波段的Radarsat-2、SIR-C/X-SAR数据进行了实验，结果表明：简缩极化熵、简缩极化比参数和简缩极化基准高度能够有效抑制疑似溢油，使海水与疑似溢油差异变小；突出溢油区域，使海水与溢油的可区分性变大。
Oil spill is one of the most common causes of marine pollution. Synthetic aperture radar (SAR) can detect marine oil spills due to its all-weather and all-day imaging capability. However
conventional algorithms using single-channel SAR usually confuses oil spills with oil spill lookalikes
making oil spill detection a challenging task. In recent years
polarimetric SAR has been studied to improve oil spill detection performance
particularly with respect to distinguishing oil spills and lookalikes. Compact polarimetric (CP) SAR is one of the most popular trends of polarimetric SAR platforms. Compared with full polarimetric SAR
CP SAR contains abundant polarization information of scattering targets. CP SAR also has large imaging range and its manufacturing cost is considerably low. Therefore
CP SAR is a promising tool for oil spill detection. In this study
we utilized CP HP-mode data and derived three parameters to distinguish oil spills from lookalikes. The three novel parameters are CP entropy (Hc)
CP fraction (PFc)
and CP pedestal height (PHc)
which are conducted from CP eigenvalue decomposition. The scattering type of sea surface is dominated by low entropy scattering. For instance
Bragg scattering from small rough surfaces can be regarded as weakly depolarized. In this vein
CP eigenvalue
$$\hat I {\gg 1}$$
http://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=8289365&type=
is much higher than
$$\hat I {\gg 2}$$
http://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=8289368&type=
which indicates the dominance of Bragg scattering. On the contrary
oil spill weakens the Bragg scattering of the ocean
and the difference between the two eigenvalues is not as high as before. Based on former consideration
Hc is high
PFc is low
and PHc is high
which means that the average scattering is in a depolarized state. The target is considered “random”
and polarization status information is lost. Hence
the aforementioned parameters can be used to detect oil spills. The threshold is determined by Otsu’s method and statistical analysis. The threshold for PFc and PHc was automatically determined by Otsu’s method
and other parameters were statistically analyzed to determine the threshold. In this study
Radarsat-2 and SIR-C/X-SAR data of C-band were used to detect oil spills. The results show that Hc
PFc
and PHc can effectively distinguish oil spills and lookalikes. The performance of all the parameters based on the CP eigenvalue decomposition is excellent in effectively excluding lookalikes
highlighting oil spill areas
and enhancing differences between oil spill and sea clutter. Moreover
the parameters are excellent in effectively maintaining details. CP SAR is promising in polarimetric SAR system because of its ability to detect a wide range of marine oil spills. The parameters derived in this study
which were based on the CP eigenvalue decomposition
can obtain satisfactory results in distinguishing oil spills from lookalikes. The quantitative experiments also confirm that the Bhattacharyya distance between oil spills and sea surface surpasses that of lookalikes
which proves that our method achieves fine oil spill detection.
Ainsworth T L, Cloude S R and Lee J S. 2002. Eigenvector analysis of polarimetric SAR data//IEEE International Geoscience and Remote Sensing Symposium. Toronto, Ontario, Canada: IEEE: 626–628 [DOI: 10.1109/IGARSS.2002.1025126 http://dx.doi.org/10.1109/IGARSS.2002.1025126 ]
Brekke C and Solberg A H S. 2005. Oil spill detection by satellite remote sensing. Remote Sensing of Environment, 95(1): 1–13
Charbonneau F J, Brisco B, Raney R K, McNairn H, Liu C, Vachon P W, Shang J, DeAbreu R, Champagne C, Merzouki A and Geldsetzer T. 2010. Compact polarimetry overview and applications assessment. Canadian Journal of Remote Sensing, 36(S2): S298–S315
Cloude S R, Goodenough D G and Chen H. 2012. Compact decomposition theory. IEEE Geoscience and Remote Sensing Letters, 9(1): 28–32
Cloude S R and Pottier E. 1996. A review of target decomposition theorems in radar polarimetry. IEEE Transactions on Geoscience and Remote Sensing, 34(2): 498–518
Li Y, Lin H, Zhang Y, et al . 2015. Comparisons of circular transmit and linear receive compact polarimetric SAR features for oil slicks discrimination. Journal of Sensors
陆应诚, 胡传民, 孙绍杰, 张民伟, 周杨, 石静, 温颜沙. 2016. 海洋溢油与烃渗漏的光学遥感研究进展. 遥感学报, 20(5): 1259–1269
Lu Y C, Hu C M, Sun S J, Zhang M W, Zhou Y, Shi J and Wen Y S. 2016. Overview of optical remote sensing of marine oil spills and hydrocarbon seepage. Journal of Remote Sensing, 20(5): 1259–1269 (
马腾波, 王思远. 2009. 基于边缘分析的海面溢油检测. 遥感学报, 13(6): 1082–1091
Ma T B and Wang S Y. 2009. Oil detection algorithm based on edge detection. Journal of Remote Sensing, 13(6): 1082–1091 (
Migliaccio M, Ferrara G, Gambardella A, Nunziata F and Sorrentino A. 2007. A physically consistent speckle model for marine SLC SAR images. IEEE Journal of Oceanic Engineering, 32(4): 839–847
Migliaccio M, Nunziata F, Brown C E, Holt B, Li X F, Pichel W and Shimada M. 2012. Polarimetric synthetic aperture radar utilized to track oil spills. EOS Transactions American Geophysical Union, 93(16): 161–162
Migliaccio M, Nunziata F and Buono A. 2015. SAR polarimetry for sea oil slick observation. International Journal of Remote Sensing, 36(12): 3243–3273
Migliaccio M, Nunziata F and Gambardella A. 2009. On the co-polarized phase difference for oil spill observation. International Journal of Remote Sensing, 30(6): 1587–1602
Minchew B, Jones C E, Holt B. 2012. Polarimetric analysis of backscatter from the deepwater horizon oil spill using l-band synthetic aperture radar. IEEE Transactions on Geoscience and Remote Sensing, 50(10): 3812–3830
Nunziata F, Migliaccio M and Gambardella A. 2011. Pedestal height for sea oil slick observation. IET Radar, Sonar and Navigation, 5(2): 103–110
Nunziata F, Migliaccio M and Li X F. 2015. Sea oil slick observation using hybrid-polarity SAR architecture. IEEE Journal of Oceanic Engineering, 40(2): 426–440
Raney R K. 2007. Hybrid-polarity SAR architecture. IEEE Transactions on Geoscience and Remote Sensing, 45(11): 3397–3404
Salberg A B, Rudjord Ø and Solberg A H S. 2012. Model based oil spill detection using polarimetric SAR//Proceedings of 2012 IEEE International Geoscience and Remote Sensing Symposium. Munich, Germany: IEEE. [DOI: 10.1109/IGARSS.2012.6352270 http://dx.doi.org/10.1109/IGARSS.2012.6352270 ]
Salberg A B, Rudjord Ø and Solberg A H S. 2014. Oil spill detection in hybrid-polarimetric SAR images. IEEE Transactions on Geoscience and Remote Sensing, 52(10): 6521–6533
Shirvany R, Chabert M and Tourneret J Y. 2012. Ship and oil-spill detection using the degree of polarization in linear and hybrid/compact dual-pol SAR. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 5(3): 885–892
Skrunes S, Brekke C and Eltoft T. 2014. Characterization of marine surface slicks by radarsat-2 multipolarization features. IEEE Transactions on Geoscience and Remote Sensing, 52(9): 5302–5319
Solberg A H S. 2012. Remote sensing of ocean oil-spill pollution. Proceedings of the IEEE, 100(10): 2931–2945
Wang W G, Lu F, Wu P and Wang J. 2010. Oil spill detection from polarimetric SAR image. Proceedings of IEEE 10th International Conference on Signal Processing. Beijing, China: IEEE: 832–835 [DOI: 10.1109/ICOSP.2010.5655943 http://dx.doi.org/10.1109/ICOSP.2010.5655943 ]
吴一全, 吉玚, 沈毅, 张宇飞. 2012. Tsallis熵和改进CV模型的海面溢油SAR图像分割. 遥感学报, 16(4): 678–690
Wu Y Q, Ji Y, Shen Y and Zhang Y F. 2012. Marine spill oil SAR image segmentation based on Tsallis entropy and improved Chan Vese model. Journal of Remote Sensing, 16(4): 678–690 (
杨帆, 杨健, 殷君君, 宋建社. 2015. 基于极化SAR分解模型的油膜检测. 清华大学学报(自然科学版), 55(8): 854–859
Yang F, Yang J, Yin J J and Song J S. 2015. Spill detection based on polarimetric SAR decomposition models. Journal of Tsinghua University (Science and Technology), 55(8): 854–859 (
Yin J J, Yang J, Zhou Z S and Song J S. 2015. The extended Bragg scattering model-based method for ship and oil-spill observation using compact polarimetric SAR. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(8): 3760–3772
Zhang B, Li X F, Perrie W, and Garcia-Pineda O. 2017. Compact polarimetric synthetic aperture radar for marine oil platform and slick detection. IEEE Transactions on Geoscience and Remote Sensing, 55(3): 1407–1423
Zhang B, Perrie W, Li X F and Pichel W G. 2011. Mapping sea surface oil slicks using RADARSAT-2 quad-polarization SAR image. Geophysical Research Letters, 38(10): L10602
郑洪磊, 张彦敏, 王运华. 2015. 基于极化特征SERD的SAR溢油检测. 海洋湖沼通报(4): 173–180
Zheng H L, Zhang Y M and Wang Y H. 2015. Oil spill detection based on polarimetric feature SERD. Transactions of Oceanology and Limnology(4): 173–180 (
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