Abstract

Reference spectral signature selection is a fundamental work for automatic oil spill detection. To address this issue, a new approach is proposed here, which employs the density-based cluster to select a specific spectral signature from a hyperspectral image. This paper first introduces the framework of oil spill detection from hyperspectral images, indicating that detecting oil spill requires a reference spectral signature of oil spill, parameters of background, and a target detection algorithm. Based on the framework, we give the new reference spectral signature selection approach in details. Then, we demonstrate the estimation of background parameters according to the reflectance of seawater in the infrared bands. Next, the conventional adaptive cosine estimator (ACE) algorithm is employed to achieve oil spill detection. Finally, the proposed approach is tested via several practical hyperspectral images that are collected during the Horizon Deep water oil spill. The experimental results show that this new approach can automatically select the reference spectral signature of oil spills from hyperspectral images and has high detection performance.

© 2016 Optical Society of America

Full Article  |  PDF Article
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References

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    [Crossref]
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    [Crossref]
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    [Crossref]
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    [Crossref]
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    [Crossref] [PubMed]
  34. D. Yu, X. Ma, Y. Tu, and L. Lai, “Both piston-like and rotational motions are present in bacterial chemoreceptor signaling,” Scientific Reports 5, 8640 (2015).
    [Crossref] [PubMed]
  35. H. Yu and Y.-S. Lin, “Toward structure prediction of cyclic peptides,” Physical Chemistry Chemical Physics 17(6), 4210–4219 (2015).
    [Crossref] [PubMed]
  36. K. Sun, X. Geng, and L. Ji, “Exemplar component analysis: A fast band selection method for hyperspectral imagery,” IEEE Geoscience and Remote Sensing Letters 12(5), 998–1002 (2015).
    [Crossref]
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    [Crossref]
  39. R. N. Clark, G. A. Swayze, K. E. Livo, R. F. Kokaly, S. J. Sutley, J. B. Dalton, R. R. McDougal, and C. A. Gent, “Imaging spectroscopy: Earth and planetary remote sensing with the usgs tetracorder and expert systems,” Journal of Geophysical Research: Planets (1991–2012) 108(E12) 5131 (2003).
    [Crossref]
  40. D. G. Manolakis, “Overview of algorithms for hyperspectral target detection: theory and practice,” Proc. SPIE 4725, 202–215 (2002).
    [Crossref]
  41. D. Manolakis, R. Lockwood, T. Cooley, and J. Jacobson, “Is there a best hyperspectral detection algorithm?” Proc. SPIE 7334, 733402 (2009).
    [Crossref]
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    [Crossref]
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    [Crossref]
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    [Crossref]

2015 (6)

C. Hu, S. Chen, M. Wang, B. Murch, and J. Taylor, “Detecting surface oil slicks using VIIRS nighttime imagery under moon glint: a case study in the Gulf of Mexico,” Remote Sensing Letters 6(4), 295–301 (2015).
[Crossref]

M. Wang and C. Hu, “Extracting Oil Slick Features From VIIRS Nighttime Imagery Using a Gaussian Filter and Morphological Constraints,” IEEE Geoscience And Remote Sensing Letters 12(10), 2051–2055 (2015).
[Crossref]

X. Li, X. Jia, L. Wang, and K. Zhao, “On spectral unmixing resolution using extended support vector machines,” IEEE Transactions on Geoscience and Remote Sensing 53(9), 4985–4996 (2015).
[Crossref]

D. Yu, X. Ma, Y. Tu, and L. Lai, “Both piston-like and rotational motions are present in bacterial chemoreceptor signaling,” Scientific Reports 5, 8640 (2015).
[Crossref] [PubMed]

H. Yu and Y.-S. Lin, “Toward structure prediction of cyclic peptides,” Physical Chemistry Chemical Physics 17(6), 4210–4219 (2015).
[Crossref] [PubMed]

K. Sun, X. Geng, and L. Ji, “Exemplar component analysis: A fast band selection method for hyperspectral imagery,” IEEE Geoscience and Remote Sensing Letters 12(5), 998–1002 (2015).
[Crossref]

2014 (6)

X. Jia and L. Wang, “Fuzzy assessment of spectral unmixing algorithms,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7(6), 1947–1955 (2014).
[Crossref]

A. Rodriguez and A. Laio, “Clustering by fast search and find of density peaks,” Science 344(6191), 1492–1496 (2014).
[Crossref] [PubMed]

I. Mezić, S. Loire, V. A. Fonoberov, and P. Hogan, “A new mixing diagnostic and Gulf oil spill movement,” Science 330(6003), 486–489 (2014).
[Crossref]

A.-B. Salberg, O. Rudjord, and A. H. S. Solberg, “Oil spill detection in hybrid-polarimetric SAR images,” IEEE Transactions on Geoscience and Remote Sensing 52(10), 6521–6533 (2014).
[Crossref]

Y. Li, Y. Zhang, J. Chen, and H. Zhang, “Improved compact polarimetric SAR quad-pol reconstruction algorithm for oil spill detection,” IEEE Geoscience and Remote Sensing Letters 11(6), 1139–1142 (2014).
[Crossref]

J. Zhao, M. Temimi, H. Ghedira, and C. Hu, “Exploring the potential of optical remote sensing for oil spill detection in shallow coastal waters-a case study in the Arabian Gulf,” Optics Express 22(11), 13755–13772 (2014).
[Crossref] [PubMed]

2013 (8)

O. Garcia-Pineda, I. MacDonald, X. Li, C. Jackson, and W. Pichel, “Oil spill mapping and measurement in the Gulf of Mexico with textural classifier neural network algorithm (TCNNA),” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 6(6), 2517–2525 (2013).
[Crossref]

Y. Lu, X. Li, Q. Tian, G. Zheng, S. Sun, Y. Liu, and Q. Yang, “Progress in Marine Oil Spill Optical Remote Sensing: Detected Targets, Spectral Response Characteristics, and Theories,” Marine Geodesy 36(3), 334–346 (2013).
[Crossref]

Y. Lu, Q. Tian, X. Wang, G. Zheng, and X. Li, “Determining oil slick thickness using hyperspectral remote sensing in the Bohai Sea of China,” International Journal Of Digital Earth 6(1), 76–93 (2013).
[Crossref]

Z. A. Otremba, “Modeling of the light transfer in a water column polluted with oil suspension,” Journal Of The European Optical Society-Rapid Publications 8, 13067 (2013).
[Crossref]

Z. Otremba, O. Zielinski, and C. Hu, “Optical contrast of oil dispersed in seawater under windy conditions,” Journal Of The European Optical Society-Rapid Publications 8, 13051 (2013).
[Crossref]

O. Garcia-Pineda, I. MacDonald, C. Hu, J. Svejkovsky, M. Hess, D. Dukhovskoy, and S. L. Morey, “Detection of Floating Oil Anomalies From the Deepwater Horizon Oil Spill With Synthetic Aperture Radar,” Oceanography 26(2), 124–137 (2013).
[Crossref]

N. U. Chowdhury, A. A. Sakla, and M. S. Alam, “Oil spill detection in ocean environment via ultrasonic imaging and spectral fringe-adjusted joint transform correlation,” Optical Engineering 52(8), 083109 (2013).
[Crossref]

R. F. Kokaly, B. R. Couvillion, J. M. Holloway, D. A. Roberts, S. L. Ustin, S. H. Peterson, S. Khanna, and S. C. Piazza, “Spectroscopic remote sensing of the distribution and persistence of oil from the Deepwater Horizon spill in Barataria Bay marshes,” Remote Sensing of Environment 129, 210–230 (2013).
[Crossref]

2012 (3)

P. Sidike, J. Khan, M. Alam, and S. Bhuiyan, “Spectral unmixing of hyperspectral data for oil spill detection,” Proc. SPIE 8498, 84981B (2012).
[Crossref]

I. Leifer, W. J. Lehr, D. Simecek-Beatty, E. Bradley, R. Clark, P. Dennison, Y. Hu, S. Matheson, C. E. Jones, B. Holt, M. Reif, D. A. Roberts, J. Svejkovsky, G. Swayze, and J. Wozencraft, “State of the art satellite and airborne marine oil spill remote sensing: Application to the BP Deepwater Horizon oil spill,” Remote Sensing of Environment 124, 185–209 (2012).
[Crossref]

Y. Lu, X. Li, Q. Tian, and W. Han, “An optical remote sensing model for estimating oil slick thickness based on two-beam interference theory,” Optics Express 20(22), 24496–24504 (2012).
[Crossref] [PubMed]

2011 (2)

Y. Lu, Q. Tian, and X. Li, “The remote sensing inversion theory of offshore oil slick thickness based on a two-beam interference model,” Science China-Earth Sciences 54(5), 678–685 (2011).
[Crossref]

R. S. Rand, R. N. Clark, and K. E. Livo, “Feature-based and statistical methods for analyzing the Deepwater Horizon oil spill with AVIRIS imagery,” Proc. SPIE 8158, 81580N (2011).
[Crossref]

2010 (3)

Y. Shu, J. Li, H. Yousif, and G. Gomes, “Dark-spot detection from SAR intensity imagery with spatial density thresholding for oil-spill monitoring,” Remote Sensing of Environment 114, 2026–2035 (2010).
[Crossref]

G. E. Machlis and M. K. McNutt, “Scenario-building for the deepwater horizon oil spill,” Science 329(5995), 1018–1019 (2010).
[Crossref] [PubMed]

Y. Li and J. Li, “Oil spill detection from SAR intensity imagery using a marked point process,” Remote Sensing of Environment 114, 1590–1601 (2010).
[Crossref]

2009 (2)

C. Hu, X. Li, W. G. Pichel, and F. E. Muller-Karger, “Detection of natural oil slicks in the NW Gulf of Mexico using MODIS imagery,” Geophysical Research Letters 36(1), L01604 (2009).
[Crossref]

D. Manolakis, R. Lockwood, T. Cooley, and J. Jacobson, “Is there a best hyperspectral detection algorithm?” Proc. SPIE 7334, 733402 (2009).
[Crossref]

2007 (1)

Z. Otremba, “Oil droplets as light absorbents in seawater,” Optics Express 15(14), 8592–8597 (2007).
[Crossref] [PubMed]

2005 (1)

C. Brekke and A. H. Solberg, “Oil spill detection by satellite remote sensing,” Remote Sensing of Environment 95(1), 1–13 (2005).
[Crossref]

2004 (1)

Z. Otremba and J. Piskozub, “Modelling the bidirectional reflectance distribution function (BRDF) of seawater polluted by an oil film,” Optics Express 12(8), 1671–1676 (2004).
[Crossref] [PubMed]

2003 (3)

Z. Otremba and J. Piskozub, “Modeling the remotely sensed optical contrast caused by oil suspended in the sea water column,” Optics Express 11(1), 2–6 (2003).
[Crossref] [PubMed]

R. N. Clark, G. A. Swayze, K. E. Livo, R. F. Kokaly, S. J. Sutley, J. B. Dalton, R. R. McDougal, and C. A. Gent, “Imaging spectroscopy: Earth and planetary remote sensing with the usgs tetracorder and expert systems,” Journal of Geophysical Research: Planets (1991–2012) 108(E12) 5131 (2003).
[Crossref]

D. Manolakis, D. Marden, and G. A. Shaw, “Hyperspectral image processing for automatic target detection applications,” Lincoln Laboratory Journal 14(1), 79–116 (2003).

2002 (2)

D. Manolakis and G. Shaw, “Detection algorithms for hyperspectral imaging applications,” IEEE Signal Processing Magazine 19(1), 29–43 (2002).
[Crossref]

D. G. Manolakis, “Overview of algorithms for hyperspectral target detection: theory and practice,” Proc. SPIE 4725, 202–215 (2002).
[Crossref]

2001 (1)

S. Kraut, L. Scharf, and L. McWhorter, “Adaptive subspace detectors,” IEEE Transactions on Signal Processing 49(1), 1–16 (2001).
[Crossref]

1999 (1)

S. Kraut and L. Scharf, “The CFAR adaptive subspace detector is a scale-invariant GLRT,” IEEE Transactions on Signal Processing 47(9), 2538–2541 (1999).
[Crossref]

1987 (1)

W. M. Porter and H. T. Enmark, “A system overview of the airborne visible/infrared imaging spectrometer (AVIRIS),” Proc. SPIE 0834, 22–31 (1987).
[Crossref]

Alam, M.

P. Sidike, J. Khan, M. Alam, and S. Bhuiyan, “Spectral unmixing of hyperspectral data for oil spill detection,” Proc. SPIE 8498, 84981B (2012).
[Crossref]

Alam, M. S.

N. U. Chowdhury, A. A. Sakla, and M. S. Alam, “Oil spill detection in ocean environment via ultrasonic imaging and spectral fringe-adjusted joint transform correlation,” Optical Engineering 52(8), 083109 (2013).
[Crossref]

Andreou, C.

D. Sykas, V. Karathanassi, C. Andreou, and P. Kolokoussis, “Oil spill thickness estimation using unmixing methods,” in Proceedings of 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, (2011), pp. 1–4.

Bhuiyan, S.

P. Sidike, J. Khan, M. Alam, and S. Bhuiyan, “Spectral unmixing of hyperspectral data for oil spill detection,” Proc. SPIE 8498, 84981B (2012).
[Crossref]

Bradley, E.

I. Leifer, W. J. Lehr, D. Simecek-Beatty, E. Bradley, R. Clark, P. Dennison, Y. Hu, S. Matheson, C. E. Jones, B. Holt, M. Reif, D. A. Roberts, J. Svejkovsky, G. Swayze, and J. Wozencraft, “State of the art satellite and airborne marine oil spill remote sensing: Application to the BP Deepwater Horizon oil spill,” Remote Sensing of Environment 124, 185–209 (2012).
[Crossref]

R. N. Clark, G. A. Swayze, I. Leifer, K. E. Livo, R. Kokaly, T. Hoefen, S. Lundeen, M. Eastwood, R. O. Green, N. Pearson, C. Sarture, I. McCubbin, D. Roberts, E. Bradley, D. Steele, T. Ryan, and R. Dominguez, “A method for quantitative mapping of thick oil spills using imaging spectroscopy,” Open-File Report1020–1167, U.S. Department of the Interior, U.S. Geological Survey (2010).

Bradley, E. S.

R. F. Kokaly, T. M. Hoefen, K. E. Livo, G. A. Swayze, I. Leifer, I. B. McCubbin, M. L. Eastwood, R. O. Green, S. R. Lundeen, C. M. Sarture, D. Steele, T. Ryan, E. S. Bradley, and D. A. Roberts, “A rapid method for creating qualitative images indicative of thick oil emulsion on the oceans surface from imaging spectrometer data,” Open-File Report1020–1107, U.S. Departmentof the Interior, U.S. Geological Survey (2010).

Brekke, C.

C. Brekke and A. H. Solberg, “Oil spill detection by satellite remote sensing,” Remote Sensing of Environment 95(1), 1–13 (2005).
[Crossref]

Chen, J.

Y. Li, Y. Zhang, J. Chen, and H. Zhang, “Improved compact polarimetric SAR quad-pol reconstruction algorithm for oil spill detection,” IEEE Geoscience and Remote Sensing Letters 11(6), 1139–1142 (2014).
[Crossref]

Chen, S.

C. Hu, S. Chen, M. Wang, B. Murch, and J. Taylor, “Detecting surface oil slicks using VIIRS nighttime imagery under moon glint: a case study in the Gulf of Mexico,” Remote Sensing Letters 6(4), 295–301 (2015).
[Crossref]

Chowdhury, N. U.

N. U. Chowdhury, A. A. Sakla, and M. S. Alam, “Oil spill detection in ocean environment via ultrasonic imaging and spectral fringe-adjusted joint transform correlation,” Optical Engineering 52(8), 083109 (2013).
[Crossref]

Clark, R.

I. Leifer, W. J. Lehr, D. Simecek-Beatty, E. Bradley, R. Clark, P. Dennison, Y. Hu, S. Matheson, C. E. Jones, B. Holt, M. Reif, D. A. Roberts, J. Svejkovsky, G. Swayze, and J. Wozencraft, “State of the art satellite and airborne marine oil spill remote sensing: Application to the BP Deepwater Horizon oil spill,” Remote Sensing of Environment 124, 185–209 (2012).
[Crossref]

Clark, R. N.

R. S. Rand, R. N. Clark, and K. E. Livo, “Feature-based and statistical methods for analyzing the Deepwater Horizon oil spill with AVIRIS imagery,” Proc. SPIE 8158, 81580N (2011).
[Crossref]

R. N. Clark, G. A. Swayze, K. E. Livo, R. F. Kokaly, S. J. Sutley, J. B. Dalton, R. R. McDougal, and C. A. Gent, “Imaging spectroscopy: Earth and planetary remote sensing with the usgs tetracorder and expert systems,” Journal of Geophysical Research: Planets (1991–2012) 108(E12) 5131 (2003).
[Crossref]

R. N. Clark, G. A. Swayze, I. Leifer, K. E. Livo, R. Kokaly, T. Hoefen, S. Lundeen, M. Eastwood, R. O. Green, N. Pearson, C. Sarture, I. McCubbin, D. Roberts, E. Bradley, D. Steele, T. Ryan, and R. Dominguez, “A method for quantitative mapping of thick oil spills using imaging spectroscopy,” Open-File Report1020–1167, U.S. Department of the Interior, U.S. Geological Survey (2010).

Cooley, T.

D. Manolakis, R. Lockwood, T. Cooley, and J. Jacobson, “Is there a best hyperspectral detection algorithm?” Proc. SPIE 7334, 733402 (2009).
[Crossref]

Couvillion, B. R.

R. F. Kokaly, B. R. Couvillion, J. M. Holloway, D. A. Roberts, S. L. Ustin, S. H. Peterson, S. Khanna, and S. C. Piazza, “Spectroscopic remote sensing of the distribution and persistence of oil from the Deepwater Horizon spill in Barataria Bay marshes,” Remote Sensing of Environment 129, 210–230 (2013).
[Crossref]

Dalton, J. B.

R. N. Clark, G. A. Swayze, K. E. Livo, R. F. Kokaly, S. J. Sutley, J. B. Dalton, R. R. McDougal, and C. A. Gent, “Imaging spectroscopy: Earth and planetary remote sensing with the usgs tetracorder and expert systems,” Journal of Geophysical Research: Planets (1991–2012) 108(E12) 5131 (2003).
[Crossref]

Dennison, P.

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O. Garcia-Pineda, I. MacDonald, C. Hu, J. Svejkovsky, M. Hess, D. Dukhovskoy, and S. L. Morey, “Detection of Floating Oil Anomalies From the Deepwater Horizon Oil Spill With Synthetic Aperture Radar,” Oceanography 26(2), 124–137 (2013).
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R. F. Kokaly, T. M. Hoefen, K. E. Livo, G. A. Swayze, I. Leifer, I. B. McCubbin, M. L. Eastwood, R. O. Green, S. R. Lundeen, C. M. Sarture, D. Steele, T. Ryan, E. S. Bradley, and D. A. Roberts, “A rapid method for creating qualitative images indicative of thick oil emulsion on the oceans surface from imaging spectrometer data,” Open-File Report1020–1107, U.S. Departmentof the Interior, U.S. Geological Survey (2010).

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J. Zhao, M. Temimi, H. Ghedira, and C. Hu, “Exploring the potential of optical remote sensing for oil spill detection in shallow coastal waters-a case study in the Arabian Gulf,” Optics Express 22(11), 13755–13772 (2014).
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R. F. Kokaly, B. R. Couvillion, J. M. Holloway, D. A. Roberts, S. L. Ustin, S. H. Peterson, S. Khanna, and S. C. Piazza, “Spectroscopic remote sensing of the distribution and persistence of oil from the Deepwater Horizon spill in Barataria Bay marshes,” Remote Sensing of Environment 129, 210–230 (2013).
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R. N. Clark, G. A. Swayze, K. E. Livo, R. F. Kokaly, S. J. Sutley, J. B. Dalton, R. R. McDougal, and C. A. Gent, “Imaging spectroscopy: Earth and planetary remote sensing with the usgs tetracorder and expert systems,” Journal of Geophysical Research: Planets (1991–2012) 108(E12) 5131 (2003).
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R. F. Kokaly, T. M. Hoefen, K. E. Livo, G. A. Swayze, I. Leifer, I. B. McCubbin, M. L. Eastwood, R. O. Green, S. R. Lundeen, C. M. Sarture, D. Steele, T. Ryan, E. S. Bradley, and D. A. Roberts, “A rapid method for creating qualitative images indicative of thick oil emulsion on the oceans surface from imaging spectrometer data,” Open-File Report1020–1107, U.S. Departmentof the Interior, U.S. Geological Survey (2010).

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D. Sykas, V. Karathanassi, C. Andreou, and P. Kolokoussis, “Oil spill thickness estimation using unmixing methods,” in Proceedings of 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, (2011), pp. 1–4.

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R. F. Kokaly, T. M. Hoefen, K. E. Livo, G. A. Swayze, I. Leifer, I. B. McCubbin, M. L. Eastwood, R. O. Green, S. R. Lundeen, C. M. Sarture, D. Steele, T. Ryan, E. S. Bradley, and D. A. Roberts, “A rapid method for creating qualitative images indicative of thick oil emulsion on the oceans surface from imaging spectrometer data,” Open-File Report1020–1107, U.S. Departmentof the Interior, U.S. Geological Survey (2010).

R. N. Clark, G. A. Swayze, I. Leifer, K. E. Livo, R. Kokaly, T. Hoefen, S. Lundeen, M. Eastwood, R. O. Green, N. Pearson, C. Sarture, I. McCubbin, D. Roberts, E. Bradley, D. Steele, T. Ryan, and R. Dominguez, “A method for quantitative mapping of thick oil spills using imaging spectroscopy,” Open-File Report1020–1167, U.S. Department of the Interior, U.S. Geological Survey (2010).

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X. Li, X. Jia, L. Wang, and K. Zhao, “On spectral unmixing resolution using extended support vector machines,” IEEE Transactions on Geoscience and Remote Sensing 53(9), 4985–4996 (2015).
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O. Garcia-Pineda, I. MacDonald, X. Li, C. Jackson, and W. Pichel, “Oil spill mapping and measurement in the Gulf of Mexico with textural classifier neural network algorithm (TCNNA),” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 6(6), 2517–2525 (2013).
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Y. Lu, X. Li, Q. Tian, G. Zheng, S. Sun, Y. Liu, and Q. Yang, “Progress in Marine Oil Spill Optical Remote Sensing: Detected Targets, Spectral Response Characteristics, and Theories,” Marine Geodesy 36(3), 334–346 (2013).
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Y. Lu, Q. Tian, X. Wang, G. Zheng, and X. Li, “Determining oil slick thickness using hyperspectral remote sensing in the Bohai Sea of China,” International Journal Of Digital Earth 6(1), 76–93 (2013).
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Y. Lu, X. Li, Q. Tian, and W. Han, “An optical remote sensing model for estimating oil slick thickness based on two-beam interference theory,” Optics Express 20(22), 24496–24504 (2012).
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Y. Lu, Q. Tian, and X. Li, “The remote sensing inversion theory of offshore oil slick thickness based on a two-beam interference model,” Science China-Earth Sciences 54(5), 678–685 (2011).
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C. Hu, X. Li, W. G. Pichel, and F. E. Muller-Karger, “Detection of natural oil slicks in the NW Gulf of Mexico using MODIS imagery,” Geophysical Research Letters 36(1), L01604 (2009).
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Y. Li and J. Li, “Oil spill detection from SAR intensity imagery using a marked point process,” Remote Sensing of Environment 114, 1590–1601 (2010).
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R. N. Clark, G. A. Swayze, K. E. Livo, R. F. Kokaly, S. J. Sutley, J. B. Dalton, R. R. McDougal, and C. A. Gent, “Imaging spectroscopy: Earth and planetary remote sensing with the usgs tetracorder and expert systems,” Journal of Geophysical Research: Planets (1991–2012) 108(E12) 5131 (2003).
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R. F. Kokaly, T. M. Hoefen, K. E. Livo, G. A. Swayze, I. Leifer, I. B. McCubbin, M. L. Eastwood, R. O. Green, S. R. Lundeen, C. M. Sarture, D. Steele, T. Ryan, E. S. Bradley, and D. A. Roberts, “A rapid method for creating qualitative images indicative of thick oil emulsion on the oceans surface from imaging spectrometer data,” Open-File Report1020–1107, U.S. Departmentof the Interior, U.S. Geological Survey (2010).

R. N. Clark, G. A. Swayze, I. Leifer, K. E. Livo, R. Kokaly, T. Hoefen, S. Lundeen, M. Eastwood, R. O. Green, N. Pearson, C. Sarture, I. McCubbin, D. Roberts, E. Bradley, D. Steele, T. Ryan, and R. Dominguez, “A method for quantitative mapping of thick oil spills using imaging spectroscopy,” Open-File Report1020–1167, U.S. Department of the Interior, U.S. Geological Survey (2010).

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D. Manolakis, R. Lockwood, T. Cooley, and J. Jacobson, “Is there a best hyperspectral detection algorithm?” Proc. SPIE 7334, 733402 (2009).
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I. Mezić, S. Loire, V. A. Fonoberov, and P. Hogan, “A new mixing diagnostic and Gulf oil spill movement,” Science 330(6003), 486–489 (2014).
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Y. Lu, X. Li, Q. Tian, G. Zheng, S. Sun, Y. Liu, and Q. Yang, “Progress in Marine Oil Spill Optical Remote Sensing: Detected Targets, Spectral Response Characteristics, and Theories,” Marine Geodesy 36(3), 334–346 (2013).
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Y. Lu, Q. Tian, X. Wang, G. Zheng, and X. Li, “Determining oil slick thickness using hyperspectral remote sensing in the Bohai Sea of China,” International Journal Of Digital Earth 6(1), 76–93 (2013).
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Y. Lu, X. Li, Q. Tian, and W. Han, “An optical remote sensing model for estimating oil slick thickness based on two-beam interference theory,” Optics Express 20(22), 24496–24504 (2012).
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Y. Lu, Q. Tian, and X. Li, “The remote sensing inversion theory of offshore oil slick thickness based on a two-beam interference model,” Science China-Earth Sciences 54(5), 678–685 (2011).
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R. N. Clark, G. A. Swayze, I. Leifer, K. E. Livo, R. Kokaly, T. Hoefen, S. Lundeen, M. Eastwood, R. O. Green, N. Pearson, C. Sarture, I. McCubbin, D. Roberts, E. Bradley, D. Steele, T. Ryan, and R. Dominguez, “A method for quantitative mapping of thick oil spills using imaging spectroscopy,” Open-File Report1020–1167, U.S. Department of the Interior, U.S. Geological Survey (2010).

Lundeen, S. R.

R. F. Kokaly, T. M. Hoefen, K. E. Livo, G. A. Swayze, I. Leifer, I. B. McCubbin, M. L. Eastwood, R. O. Green, S. R. Lundeen, C. M. Sarture, D. Steele, T. Ryan, E. S. Bradley, and D. A. Roberts, “A rapid method for creating qualitative images indicative of thick oil emulsion on the oceans surface from imaging spectrometer data,” Open-File Report1020–1107, U.S. Departmentof the Interior, U.S. Geological Survey (2010).

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D. Yu, X. Ma, Y. Tu, and L. Lai, “Both piston-like and rotational motions are present in bacterial chemoreceptor signaling,” Scientific Reports 5, 8640 (2015).
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O. Garcia-Pineda, I. MacDonald, X. Li, C. Jackson, and W. Pichel, “Oil spill mapping and measurement in the Gulf of Mexico with textural classifier neural network algorithm (TCNNA),” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 6(6), 2517–2525 (2013).
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O. Garcia-Pineda, I. MacDonald, C. Hu, J. Svejkovsky, M. Hess, D. Dukhovskoy, and S. L. Morey, “Detection of Floating Oil Anomalies From the Deepwater Horizon Oil Spill With Synthetic Aperture Radar,” Oceanography 26(2), 124–137 (2013).
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D. Manolakis, R. Lockwood, T. Cooley, and J. Jacobson, “Is there a best hyperspectral detection algorithm?” Proc. SPIE 7334, 733402 (2009).
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D. Manolakis, D. Marden, and G. A. Shaw, “Hyperspectral image processing for automatic target detection applications,” Lincoln Laboratory Journal 14(1), 79–116 (2003).

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I. Leifer, W. J. Lehr, D. Simecek-Beatty, E. Bradley, R. Clark, P. Dennison, Y. Hu, S. Matheson, C. E. Jones, B. Holt, M. Reif, D. A. Roberts, J. Svejkovsky, G. Swayze, and J. Wozencraft, “State of the art satellite and airborne marine oil spill remote sensing: Application to the BP Deepwater Horizon oil spill,” Remote Sensing of Environment 124, 185–209 (2012).
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McCubbin, I.

R. N. Clark, G. A. Swayze, I. Leifer, K. E. Livo, R. Kokaly, T. Hoefen, S. Lundeen, M. Eastwood, R. O. Green, N. Pearson, C. Sarture, I. McCubbin, D. Roberts, E. Bradley, D. Steele, T. Ryan, and R. Dominguez, “A method for quantitative mapping of thick oil spills using imaging spectroscopy,” Open-File Report1020–1167, U.S. Department of the Interior, U.S. Geological Survey (2010).

McCubbin, I. B.

R. F. Kokaly, T. M. Hoefen, K. E. Livo, G. A. Swayze, I. Leifer, I. B. McCubbin, M. L. Eastwood, R. O. Green, S. R. Lundeen, C. M. Sarture, D. Steele, T. Ryan, E. S. Bradley, and D. A. Roberts, “A rapid method for creating qualitative images indicative of thick oil emulsion on the oceans surface from imaging spectrometer data,” Open-File Report1020–1107, U.S. Departmentof the Interior, U.S. Geological Survey (2010).

McDougal, R. R.

R. N. Clark, G. A. Swayze, K. E. Livo, R. F. Kokaly, S. J. Sutley, J. B. Dalton, R. R. McDougal, and C. A. Gent, “Imaging spectroscopy: Earth and planetary remote sensing with the usgs tetracorder and expert systems,” Journal of Geophysical Research: Planets (1991–2012) 108(E12) 5131 (2003).
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O. Garcia-Pineda, I. MacDonald, C. Hu, J. Svejkovsky, M. Hess, D. Dukhovskoy, and S. L. Morey, “Detection of Floating Oil Anomalies From the Deepwater Horizon Oil Spill With Synthetic Aperture Radar,” Oceanography 26(2), 124–137 (2013).
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Muller-Karger, F. E.

C. Hu, X. Li, W. G. Pichel, and F. E. Muller-Karger, “Detection of natural oil slicks in the NW Gulf of Mexico using MODIS imagery,” Geophysical Research Letters 36(1), L01604 (2009).
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Murch, B.

C. Hu, S. Chen, M. Wang, B. Murch, and J. Taylor, “Detecting surface oil slicks using VIIRS nighttime imagery under moon glint: a case study in the Gulf of Mexico,” Remote Sensing Letters 6(4), 295–301 (2015).
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Z. Otremba, O. Zielinski, and C. Hu, “Optical contrast of oil dispersed in seawater under windy conditions,” Journal Of The European Optical Society-Rapid Publications 8, 13051 (2013).
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Z. Otremba, “Oil droplets as light absorbents in seawater,” Optics Express 15(14), 8592–8597 (2007).
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Z. Otremba and J. Piskozub, “Modelling the bidirectional reflectance distribution function (BRDF) of seawater polluted by an oil film,” Optics Express 12(8), 1671–1676 (2004).
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Z. Otremba and J. Piskozub, “Modeling the remotely sensed optical contrast caused by oil suspended in the sea water column,” Optics Express 11(1), 2–6 (2003).
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Peterson, S. H.

R. F. Kokaly, B. R. Couvillion, J. M. Holloway, D. A. Roberts, S. L. Ustin, S. H. Peterson, S. Khanna, and S. C. Piazza, “Spectroscopic remote sensing of the distribution and persistence of oil from the Deepwater Horizon spill in Barataria Bay marshes,” Remote Sensing of Environment 129, 210–230 (2013).
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Piazza, S. C.

R. F. Kokaly, B. R. Couvillion, J. M. Holloway, D. A. Roberts, S. L. Ustin, S. H. Peterson, S. Khanna, and S. C. Piazza, “Spectroscopic remote sensing of the distribution and persistence of oil from the Deepwater Horizon spill in Barataria Bay marshes,” Remote Sensing of Environment 129, 210–230 (2013).
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O. Garcia-Pineda, I. MacDonald, X. Li, C. Jackson, and W. Pichel, “Oil spill mapping and measurement in the Gulf of Mexico with textural classifier neural network algorithm (TCNNA),” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 6(6), 2517–2525 (2013).
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Pichel, W. G.

C. Hu, X. Li, W. G. Pichel, and F. E. Muller-Karger, “Detection of natural oil slicks in the NW Gulf of Mexico using MODIS imagery,” Geophysical Research Letters 36(1), L01604 (2009).
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Piskozub, J.

Z. Otremba and J. Piskozub, “Modelling the bidirectional reflectance distribution function (BRDF) of seawater polluted by an oil film,” Optics Express 12(8), 1671–1676 (2004).
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Z. Otremba and J. Piskozub, “Modeling the remotely sensed optical contrast caused by oil suspended in the sea water column,” Optics Express 11(1), 2–6 (2003).
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Roberts, D.

R. N. Clark, G. A. Swayze, I. Leifer, K. E. Livo, R. Kokaly, T. Hoefen, S. Lundeen, M. Eastwood, R. O. Green, N. Pearson, C. Sarture, I. McCubbin, D. Roberts, E. Bradley, D. Steele, T. Ryan, and R. Dominguez, “A method for quantitative mapping of thick oil spills using imaging spectroscopy,” Open-File Report1020–1167, U.S. Department of the Interior, U.S. Geological Survey (2010).

Roberts, D. A.

R. F. Kokaly, B. R. Couvillion, J. M. Holloway, D. A. Roberts, S. L. Ustin, S. H. Peterson, S. Khanna, and S. C. Piazza, “Spectroscopic remote sensing of the distribution and persistence of oil from the Deepwater Horizon spill in Barataria Bay marshes,” Remote Sensing of Environment 129, 210–230 (2013).
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I. Leifer, W. J. Lehr, D. Simecek-Beatty, E. Bradley, R. Clark, P. Dennison, Y. Hu, S. Matheson, C. E. Jones, B. Holt, M. Reif, D. A. Roberts, J. Svejkovsky, G. Swayze, and J. Wozencraft, “State of the art satellite and airborne marine oil spill remote sensing: Application to the BP Deepwater Horizon oil spill,” Remote Sensing of Environment 124, 185–209 (2012).
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R. F. Kokaly, T. M. Hoefen, K. E. Livo, G. A. Swayze, I. Leifer, I. B. McCubbin, M. L. Eastwood, R. O. Green, S. R. Lundeen, C. M. Sarture, D. Steele, T. Ryan, E. S. Bradley, and D. A. Roberts, “A rapid method for creating qualitative images indicative of thick oil emulsion on the oceans surface from imaging spectrometer data,” Open-File Report1020–1107, U.S. Departmentof the Interior, U.S. Geological Survey (2010).

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A.-B. Salberg, O. Rudjord, and A. H. S. Solberg, “Oil spill detection in hybrid-polarimetric SAR images,” IEEE Transactions on Geoscience and Remote Sensing 52(10), 6521–6533 (2014).
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Ryan, T.

R. F. Kokaly, T. M. Hoefen, K. E. Livo, G. A. Swayze, I. Leifer, I. B. McCubbin, M. L. Eastwood, R. O. Green, S. R. Lundeen, C. M. Sarture, D. Steele, T. Ryan, E. S. Bradley, and D. A. Roberts, “A rapid method for creating qualitative images indicative of thick oil emulsion on the oceans surface from imaging spectrometer data,” Open-File Report1020–1107, U.S. Departmentof the Interior, U.S. Geological Survey (2010).

R. N. Clark, G. A. Swayze, I. Leifer, K. E. Livo, R. Kokaly, T. Hoefen, S. Lundeen, M. Eastwood, R. O. Green, N. Pearson, C. Sarture, I. McCubbin, D. Roberts, E. Bradley, D. Steele, T. Ryan, and R. Dominguez, “A method for quantitative mapping of thick oil spills using imaging spectroscopy,” Open-File Report1020–1167, U.S. Department of the Interior, U.S. Geological Survey (2010).

Sakla, A. A.

N. U. Chowdhury, A. A. Sakla, and M. S. Alam, “Oil spill detection in ocean environment via ultrasonic imaging and spectral fringe-adjusted joint transform correlation,” Optical Engineering 52(8), 083109 (2013).
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Salberg, A.-B.

A.-B. Salberg, O. Rudjord, and A. H. S. Solberg, “Oil spill detection in hybrid-polarimetric SAR images,” IEEE Transactions on Geoscience and Remote Sensing 52(10), 6521–6533 (2014).
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Sarture, C.

R. N. Clark, G. A. Swayze, I. Leifer, K. E. Livo, R. Kokaly, T. Hoefen, S. Lundeen, M. Eastwood, R. O. Green, N. Pearson, C. Sarture, I. McCubbin, D. Roberts, E. Bradley, D. Steele, T. Ryan, and R. Dominguez, “A method for quantitative mapping of thick oil spills using imaging spectroscopy,” Open-File Report1020–1167, U.S. Department of the Interior, U.S. Geological Survey (2010).

Sarture, C. M.

R. F. Kokaly, T. M. Hoefen, K. E. Livo, G. A. Swayze, I. Leifer, I. B. McCubbin, M. L. Eastwood, R. O. Green, S. R. Lundeen, C. M. Sarture, D. Steele, T. Ryan, E. S. Bradley, and D. A. Roberts, “A rapid method for creating qualitative images indicative of thick oil emulsion on the oceans surface from imaging spectrometer data,” Open-File Report1020–1107, U.S. Departmentof the Interior, U.S. Geological Survey (2010).

Scharf, L.

S. Kraut, L. Scharf, and L. McWhorter, “Adaptive subspace detectors,” IEEE Transactions on Signal Processing 49(1), 1–16 (2001).
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S. Kraut and L. Scharf, “The CFAR adaptive subspace detector is a scale-invariant GLRT,” IEEE Transactions on Signal Processing 47(9), 2538–2541 (1999).
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D. Manolakis and G. Shaw, “Detection algorithms for hyperspectral imaging applications,” IEEE Signal Processing Magazine 19(1), 29–43 (2002).
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D. Manolakis, D. Marden, and G. A. Shaw, “Hyperspectral image processing for automatic target detection applications,” Lincoln Laboratory Journal 14(1), 79–116 (2003).

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Y. Shu, J. Li, H. Yousif, and G. Gomes, “Dark-spot detection from SAR intensity imagery with spatial density thresholding for oil-spill monitoring,” Remote Sensing of Environment 114, 2026–2035 (2010).
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A.-B. Salberg, O. Rudjord, and A. H. S. Solberg, “Oil spill detection in hybrid-polarimetric SAR images,” IEEE Transactions on Geoscience and Remote Sensing 52(10), 6521–6533 (2014).
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Steele, D.

R. F. Kokaly, T. M. Hoefen, K. E. Livo, G. A. Swayze, I. Leifer, I. B. McCubbin, M. L. Eastwood, R. O. Green, S. R. Lundeen, C. M. Sarture, D. Steele, T. Ryan, E. S. Bradley, and D. A. Roberts, “A rapid method for creating qualitative images indicative of thick oil emulsion on the oceans surface from imaging spectrometer data,” Open-File Report1020–1107, U.S. Departmentof the Interior, U.S. Geological Survey (2010).

R. N. Clark, G. A. Swayze, I. Leifer, K. E. Livo, R. Kokaly, T. Hoefen, S. Lundeen, M. Eastwood, R. O. Green, N. Pearson, C. Sarture, I. McCubbin, D. Roberts, E. Bradley, D. Steele, T. Ryan, and R. Dominguez, “A method for quantitative mapping of thick oil spills using imaging spectroscopy,” Open-File Report1020–1167, U.S. Department of the Interior, U.S. Geological Survey (2010).

Sun, K.

K. Sun, X. Geng, and L. Ji, “Exemplar component analysis: A fast band selection method for hyperspectral imagery,” IEEE Geoscience and Remote Sensing Letters 12(5), 998–1002 (2015).
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Sun, S.

Y. Lu, X. Li, Q. Tian, G. Zheng, S. Sun, Y. Liu, and Q. Yang, “Progress in Marine Oil Spill Optical Remote Sensing: Detected Targets, Spectral Response Characteristics, and Theories,” Marine Geodesy 36(3), 334–346 (2013).
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Sutley, S. J.

R. N. Clark, G. A. Swayze, K. E. Livo, R. F. Kokaly, S. J. Sutley, J. B. Dalton, R. R. McDougal, and C. A. Gent, “Imaging spectroscopy: Earth and planetary remote sensing with the usgs tetracorder and expert systems,” Journal of Geophysical Research: Planets (1991–2012) 108(E12) 5131 (2003).
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Svejkovsky, J.

O. Garcia-Pineda, I. MacDonald, C. Hu, J. Svejkovsky, M. Hess, D. Dukhovskoy, and S. L. Morey, “Detection of Floating Oil Anomalies From the Deepwater Horizon Oil Spill With Synthetic Aperture Radar,” Oceanography 26(2), 124–137 (2013).
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I. Leifer, W. J. Lehr, D. Simecek-Beatty, E. Bradley, R. Clark, P. Dennison, Y. Hu, S. Matheson, C. E. Jones, B. Holt, M. Reif, D. A. Roberts, J. Svejkovsky, G. Swayze, and J. Wozencraft, “State of the art satellite and airborne marine oil spill remote sensing: Application to the BP Deepwater Horizon oil spill,” Remote Sensing of Environment 124, 185–209 (2012).
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Swayze, G.

I. Leifer, W. J. Lehr, D. Simecek-Beatty, E. Bradley, R. Clark, P. Dennison, Y. Hu, S. Matheson, C. E. Jones, B. Holt, M. Reif, D. A. Roberts, J. Svejkovsky, G. Swayze, and J. Wozencraft, “State of the art satellite and airborne marine oil spill remote sensing: Application to the BP Deepwater Horizon oil spill,” Remote Sensing of Environment 124, 185–209 (2012).
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Swayze, G. A.

R. N. Clark, G. A. Swayze, K. E. Livo, R. F. Kokaly, S. J. Sutley, J. B. Dalton, R. R. McDougal, and C. A. Gent, “Imaging spectroscopy: Earth and planetary remote sensing with the usgs tetracorder and expert systems,” Journal of Geophysical Research: Planets (1991–2012) 108(E12) 5131 (2003).
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R. F. Kokaly, T. M. Hoefen, K. E. Livo, G. A. Swayze, I. Leifer, I. B. McCubbin, M. L. Eastwood, R. O. Green, S. R. Lundeen, C. M. Sarture, D. Steele, T. Ryan, E. S. Bradley, and D. A. Roberts, “A rapid method for creating qualitative images indicative of thick oil emulsion on the oceans surface from imaging spectrometer data,” Open-File Report1020–1107, U.S. Departmentof the Interior, U.S. Geological Survey (2010).

R. N. Clark, G. A. Swayze, I. Leifer, K. E. Livo, R. Kokaly, T. Hoefen, S. Lundeen, M. Eastwood, R. O. Green, N. Pearson, C. Sarture, I. McCubbin, D. Roberts, E. Bradley, D. Steele, T. Ryan, and R. Dominguez, “A method for quantitative mapping of thick oil spills using imaging spectroscopy,” Open-File Report1020–1167, U.S. Department of the Interior, U.S. Geological Survey (2010).

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Taylor, J.

C. Hu, S. Chen, M. Wang, B. Murch, and J. Taylor, “Detecting surface oil slicks using VIIRS nighttime imagery under moon glint: a case study in the Gulf of Mexico,” Remote Sensing Letters 6(4), 295–301 (2015).
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Temimi, M.

J. Zhao, M. Temimi, H. Ghedira, and C. Hu, “Exploring the potential of optical remote sensing for oil spill detection in shallow coastal waters-a case study in the Arabian Gulf,” Optics Express 22(11), 13755–13772 (2014).
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Y. Lu, X. Li, Q. Tian, G. Zheng, S. Sun, Y. Liu, and Q. Yang, “Progress in Marine Oil Spill Optical Remote Sensing: Detected Targets, Spectral Response Characteristics, and Theories,” Marine Geodesy 36(3), 334–346 (2013).
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Y. Lu, Q. Tian, X. Wang, G. Zheng, and X. Li, “Determining oil slick thickness using hyperspectral remote sensing in the Bohai Sea of China,” International Journal Of Digital Earth 6(1), 76–93 (2013).
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D. Yu, X. Ma, Y. Tu, and L. Lai, “Both piston-like and rotational motions are present in bacterial chemoreceptor signaling,” Scientific Reports 5, 8640 (2015).
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Ustin, S. L.

R. F. Kokaly, B. R. Couvillion, J. M. Holloway, D. A. Roberts, S. L. Ustin, S. H. Peterson, S. Khanna, and S. C. Piazza, “Spectroscopic remote sensing of the distribution and persistence of oil from the Deepwater Horizon spill in Barataria Bay marshes,” Remote Sensing of Environment 129, 210–230 (2013).
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Wang, L.

X. Li, X. Jia, L. Wang, and K. Zhao, “On spectral unmixing resolution using extended support vector machines,” IEEE Transactions on Geoscience and Remote Sensing 53(9), 4985–4996 (2015).
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X. Jia and L. Wang, “Fuzzy assessment of spectral unmixing algorithms,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7(6), 1947–1955 (2014).
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Wang, M.

M. Wang and C. Hu, “Extracting Oil Slick Features From VIIRS Nighttime Imagery Using a Gaussian Filter and Morphological Constraints,” IEEE Geoscience And Remote Sensing Letters 12(10), 2051–2055 (2015).
[Crossref]

C. Hu, S. Chen, M. Wang, B. Murch, and J. Taylor, “Detecting surface oil slicks using VIIRS nighttime imagery under moon glint: a case study in the Gulf of Mexico,” Remote Sensing Letters 6(4), 295–301 (2015).
[Crossref]

Wang, X.

Y. Lu, Q. Tian, X. Wang, G. Zheng, and X. Li, “Determining oil slick thickness using hyperspectral remote sensing in the Bohai Sea of China,” International Journal Of Digital Earth 6(1), 76–93 (2013).
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Wozencraft, J.

I. Leifer, W. J. Lehr, D. Simecek-Beatty, E. Bradley, R. Clark, P. Dennison, Y. Hu, S. Matheson, C. E. Jones, B. Holt, M. Reif, D. A. Roberts, J. Svejkovsky, G. Swayze, and J. Wozencraft, “State of the art satellite and airborne marine oil spill remote sensing: Application to the BP Deepwater Horizon oil spill,” Remote Sensing of Environment 124, 185–209 (2012).
[Crossref]

Yang, Q.

Y. Lu, X. Li, Q. Tian, G. Zheng, S. Sun, Y. Liu, and Q. Yang, “Progress in Marine Oil Spill Optical Remote Sensing: Detected Targets, Spectral Response Characteristics, and Theories,” Marine Geodesy 36(3), 334–346 (2013).
[Crossref]

Yousif, H.

Y. Shu, J. Li, H. Yousif, and G. Gomes, “Dark-spot detection from SAR intensity imagery with spatial density thresholding for oil-spill monitoring,” Remote Sensing of Environment 114, 2026–2035 (2010).
[Crossref]

Yu, D.

D. Yu, X. Ma, Y. Tu, and L. Lai, “Both piston-like and rotational motions are present in bacterial chemoreceptor signaling,” Scientific Reports 5, 8640 (2015).
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H. Yu and Y.-S. Lin, “Toward structure prediction of cyclic peptides,” Physical Chemistry Chemical Physics 17(6), 4210–4219 (2015).
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Y. Li, Y. Zhang, J. Chen, and H. Zhang, “Improved compact polarimetric SAR quad-pol reconstruction algorithm for oil spill detection,” IEEE Geoscience and Remote Sensing Letters 11(6), 1139–1142 (2014).
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Zhang, Y.

Y. Li, Y. Zhang, J. Chen, and H. Zhang, “Improved compact polarimetric SAR quad-pol reconstruction algorithm for oil spill detection,” IEEE Geoscience and Remote Sensing Letters 11(6), 1139–1142 (2014).
[Crossref]

Zhao, J.

J. Zhao, M. Temimi, H. Ghedira, and C. Hu, “Exploring the potential of optical remote sensing for oil spill detection in shallow coastal waters-a case study in the Arabian Gulf,” Optics Express 22(11), 13755–13772 (2014).
[Crossref] [PubMed]

Zhao, K.

X. Li, X. Jia, L. Wang, and K. Zhao, “On spectral unmixing resolution using extended support vector machines,” IEEE Transactions on Geoscience and Remote Sensing 53(9), 4985–4996 (2015).
[Crossref]

Zheng, G.

Y. Lu, X. Li, Q. Tian, G. Zheng, S. Sun, Y. Liu, and Q. Yang, “Progress in Marine Oil Spill Optical Remote Sensing: Detected Targets, Spectral Response Characteristics, and Theories,” Marine Geodesy 36(3), 334–346 (2013).
[Crossref]

Y. Lu, Q. Tian, X. Wang, G. Zheng, and X. Li, “Determining oil slick thickness using hyperspectral remote sensing in the Bohai Sea of China,” International Journal Of Digital Earth 6(1), 76–93 (2013).
[Crossref]

Zielinski, O.

Z. Otremba, O. Zielinski, and C. Hu, “Optical contrast of oil dispersed in seawater under windy conditions,” Journal Of The European Optical Society-Rapid Publications 8, 13051 (2013).
[Crossref]

Geophysical Research Letters (1)

C. Hu, X. Li, W. G. Pichel, and F. E. Muller-Karger, “Detection of natural oil slicks in the NW Gulf of Mexico using MODIS imagery,” Geophysical Research Letters 36(1), L01604 (2009).
[Crossref]

IEEE Geoscience And Remote Sensing Letters (1)

M. Wang and C. Hu, “Extracting Oil Slick Features From VIIRS Nighttime Imagery Using a Gaussian Filter and Morphological Constraints,” IEEE Geoscience And Remote Sensing Letters 12(10), 2051–2055 (2015).
[Crossref]

Y. Li, Y. Zhang, J. Chen, and H. Zhang, “Improved compact polarimetric SAR quad-pol reconstruction algorithm for oil spill detection,” IEEE Geoscience and Remote Sensing Letters 11(6), 1139–1142 (2014).
[Crossref]

K. Sun, X. Geng, and L. Ji, “Exemplar component analysis: A fast band selection method for hyperspectral imagery,” IEEE Geoscience and Remote Sensing Letters 12(5), 998–1002 (2015).
[Crossref]

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2)

O. Garcia-Pineda, I. MacDonald, X. Li, C. Jackson, and W. Pichel, “Oil spill mapping and measurement in the Gulf of Mexico with textural classifier neural network algorithm (TCNNA),” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 6(6), 2517–2525 (2013).
[Crossref]

X. Jia and L. Wang, “Fuzzy assessment of spectral unmixing algorithms,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7(6), 1947–1955 (2014).
[Crossref]

IEEE Signal Processing Magazine (1)

D. Manolakis and G. Shaw, “Detection algorithms for hyperspectral imaging applications,” IEEE Signal Processing Magazine 19(1), 29–43 (2002).
[Crossref]

IEEE Transactions on Geoscience and Remote Sensing (2)

X. Li, X. Jia, L. Wang, and K. Zhao, “On spectral unmixing resolution using extended support vector machines,” IEEE Transactions on Geoscience and Remote Sensing 53(9), 4985–4996 (2015).
[Crossref]

A.-B. Salberg, O. Rudjord, and A. H. S. Solberg, “Oil spill detection in hybrid-polarimetric SAR images,” IEEE Transactions on Geoscience and Remote Sensing 52(10), 6521–6533 (2014).
[Crossref]

IEEE Transactions on Signal Processing (2)

S. Kraut and L. Scharf, “The CFAR adaptive subspace detector is a scale-invariant GLRT,” IEEE Transactions on Signal Processing 47(9), 2538–2541 (1999).
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Journal Of The European Optical Society-Rapid Publications (2)

Z. A. Otremba, “Modeling of the light transfer in a water column polluted with oil suspension,” Journal Of The European Optical Society-Rapid Publications 8, 13067 (2013).
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D. Manolakis, D. Marden, and G. A. Shaw, “Hyperspectral image processing for automatic target detection applications,” Lincoln Laboratory Journal 14(1), 79–116 (2003).

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Figures (7)

Fig. 1
Fig. 1

Reflectance of oil, cloud, and seawater.

Fig. 2
Fig. 2

A decision graph and its corresponding spectral signature.

Fig. 3
Fig. 3

Execution of the proposed reference spectral signature selection approach.

Fig. 4
Fig. 4

False color images of test hyperspectral images. (a) Scene 1, (b) Scene 2, (c) Scene 3, (d) Scene 4, (e) Scene 5, (f) Scene 6.

Fig. 5
Fig. 5

Decision graphs and selected points. (a) Scene 1, (b) Scene 2, (c) Scene 3, (d) Scene 4, (e) Scene 5, (f) Scene 6.

Fig. 6
Fig. 6

Selected spectral signatures. (a) Scene 1, (b) Scene 2, (c) Scene 3, (d) Scene 4.

Fig. 7
Fig. 7

Oil spill detection results. (a) Scene 1, (b) Scene 2, (c) Scene 3, (d) Scene 4.

Equations (30)

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Λ ( x ) = f ( x ; θ 1 | H 1 = oil ) f ( x ; θ 0 | H 0 = seawater ) H 0 H 1 η
d ( i , j ) = x ( i ) x ( j ) x ( i ) x ( j )
ρ ( i ) = j χ [ ( d ( i , j ) ]
χ ( x ) = { 1 , x < d c 0 , otherwise
χ ( x ) = exp [ ( x d c ) 2 ]
δ ( i ) = min j : ρ ( j ) > ρ ( i ) [ d ( i , j ) ]
x ( m d , n d ) = 1 W d 2 l m = 1 , l n = 1 W d , W d x ( m + l m , n + l n )
x n b o ( k ) = x b o ( k ) x c b o ( k )
x n b ( k ) = x b ( k ) x c b ( k )
b = x n b x n b o ( x n b x n b o ) / N f x n b o 2 ( x n b o ) 2 / N f
b g = x n b x n b o ( x n b x n b o ) / N f x n b 2 ( x n b ) 2 / N f
α = b b g
β = 1 1 + ( k s k o s k t ) 4
f m = α β
f b = m f m
ρ n ( i ) = ρ ( i ) ρ min ρ max ρ min
f c ( i ) = ρ n ( i ) f b
f m = max f c ( i )
f o s = { 1 , f m τ s p 0 , f m < τ s p
ρ m = max l m = 1 , l n = 1 W d , W d [ ρ ( m f + l m , n f + l n ) ]
r b = 1 K r K l + 1 k = K l K r x ( k )
l b = { 1 , r b τ r 0 , r b < τ r
m b = 1 N b l b ( i ) = 1 x ( i )
C b = 1 N b 1 l b ( i ) = 1 [ x ( i ) m b ] [ x ( i ) m b ] T
x = p = 1 N p α p s p
p = 1 N p α p = 1
α p 0
{ H 0 : x = n b H 1 : x = s α + σ n b
n b N ( 0 , C b )
T A C E 2 = ( s T C b 1 x ) 2 ( s T C b 1 s ) ( x T C b 1 x )

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