Object detection by spectropolarimeteric imagery fusion

IEEE Transactions on Geoscience and Remote Sensing

Volumn 46, Issue 10, 2008, Pages 3337-3345

  Zhao, Yong Qiang ^a   Gong, Peng ^b,c   Pan, Quan ^a  

^a NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

^b STATE KEY LABORATORY OF REMOTE SENSING SCIENCE   (China)

^c BEIJING NORMAL UNIVERSITY   (China)

Author keywords

Anomaly detection; Fuzzy integral; Imaging spectropolarimetry; Information fusion; Spectropolarimetric projection

Indexed keywords

ALARM SYSTEMS; DATA FUSION; ELECTRIC FIELDS; ELECTROMAGNETISM; FEATURE EXTRACTION; FUSION REACTIONS; IMAGE SENSORS; INTEGRAL EQUATIONS; LIGHT MEASUREMENT; MAGNETIC MATERIALS; POLAROGRAPHIC ANALYSIS; QUERY PROCESSING; SIGNAL DETECTION;

ANOMALY DETECTION; FUZZY INTEGRAL; IMAGING SPECTROPOLARIMETRY; INFORMATION FUSION; SPECTROPOLARIMETRIC PROJECTION;

POLARIMETERS;

EID: 53849083496     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2008.920467     Document Type: Conference Paper

References (35)

1. D.Manolakis and G. Shaw, "Detection algorithms for hyperspectral imaging applications," IEEE Signal Process. Mag., vol. 19, no. 1, pp. 29-43, Jan. 2002.
2. D. W. J. Stein, S. G. Beaven, L. E. Hoff et al., "Anomaly detection from hyperspectral imagery," IEEE Signal Process. Mag., vol. 19, no. 1, pp. 58-69, Jan. 2002.
3. A. Filippidis, L. C. Jain, and N. M. Martin, "Using genetic algorithm and neural networks for surface land mine detection," IEEE Trans. Signal Process., vol. 47, no. 1, pp. 176-186, Jan. 2001.
4. C. Frank, D. W. Jong, and K. Schutte, "Infrared polarization measurements and modeling applied to surface-laid antipersonnel landmines," Opt. Eng., vol. 41, no. 5, pp. 1021-1032, May 2002.
5. P. Goovaerts, G. M. Jacquez, and A. Marcus, "Geostatistical and local cluster analysis of high resolution hyperspectral imagery for detection anomalies," Remote Sens. Environ., vol. 95, no. 3, pp. 351-367, Apr. 2005.
6. D. S. Sabatke, A. M. Locke, E. L. Dereniak et al., "Linear calibration and reconstruction techniques for channeled spectropolarimetry, " Opt. Express, vol. 11, no. 22, pp. 2940-2952, Nov. 2003.
7. J. S. Tyo and T. S. Turner, Jr., "Variable-retardance, Fourier-transform imaging spectropolarimeters for visible spectrum remote sensing," Appl. Opt., vol. 40, no. 9, pp. 1450-1458, Sep. 2001.
8. L. B. Wolff, "Polarization vision: A new sensory approach to image understanding," Image Vis. Comput., vol. 15, no. 2, pp. 81-93, Feb. 1997.
9. L. B.Wolff and A. G. Andreou, "Polarization camera sensors," Image Vis. Comput., vol. 12, no. 6, pp. 497-510, Aug. 1995.
10. M. Born and E. Wolf, Principles of Optics. Cambridge, U.K.: Cambridge Univ. Press, ch. 10, pp. 619-624.
11. H. Kurosaki, H. Koshiishi, T. Suzuki et al., "Development of tunable imaging spectro-polarimeter for remote sensing," Adv. Space Res., vol. 32, no. 11, pp. 2141-2146, Dec. 2003.
12. N. Gata, "Imaging spectroscopy using tunable filters: A review," in Proc. SPIE-Wavelet Applications VII, H. H. Szu, M. Vetterli, W. J. Campbell, and R. Buss, Eds., Apr. 2000, vol. 4056, pp. 50-64.
13. N. Gat and J. Buss, "Full Stokes' vector extraction with imaging spectro-polarimetry using a liquid crystal variable retarder and a liquid crystal tunable filter," Detection & Classification Difficult Targets, US Army Aviation & Missile Command, pp. 25-26, Sep. 2002, Redstone Arsenal, AL.
14. D. Manolakis, D. Marden, and G. A. Shaw, "Hyperspectral image processing for automatic target detection applications," Linc. Lab. J., vol. 14, no. 1, pp. 79-100, 2003.
15. D. Manolakis, C. Siracusa, and G. A. Shaw, "Adaptive matched subspace detectors for hyperspectral imaging applications," in IEEE Int. Conf. Acoust., Speech, Signal Process., Salt Lake City, UT, May 2001, vol. 5, pp. 3153-3156.
16. C.-I Chang and S.-S. Chiang, "Anomaly detection and classification for hyperspectral imagery," IEEE Trans. Geosci. Remote Sens., vol. 40, no. 6, pp. 1314-1325, Jun. 2002.
17. I. S. Reed and X. Yu, "Adaptive multi-band CFAR detection of an optional pattern with unknown spectral distribution," IEEE Trans. Acoust., Speech, Signal Process., vol. 38, no. 10, pp. 1760-1770, Oct. 1990.
18. Y.-Q. Zhao, Q. Pan, and H.-C. Zhang, "New polarization imaging method based on spatially adaptive wavelet image fusion," Opt. Eng., vol. 4, no. 12, p. 123 202, Dec. 2006.
19. L. M. Novak and M. C. Burl, "Optimal speckle reduction in polarimetric SAR imagery," IEEE Trans. Aerosp. Electron. Syst., vol. 26, no. 2, pp. 293-305, Mar. 1990.
20. A. Lopes and F. Sery, "Optimal speckle reduction for the product model in multilook polarimetric SAR imagery and the Wishart distribution," IEEE Trans. Geosci. Remote Sens., vol. 35, no. 3, pp. 632-647, May 1997.
21. D. H. Lee and D. Park, "An effect algorithm for fuzzy weighted average," Fuzzy Sets Syst., vol. 87, no. 1, pp. 39-45, Apr. 1997.
22. J. M. Keller and J. Osborn, "Training the fuzzy integral," Int. J. Approx. Reason., vol. 15, no. 1, pp. 1-24, Jul. 1996.
23. S. Auephanwiriyakul, J. M. Keller, and P. D. Gader, "General Choquet fuzzy integral fusion," Inf. Fusion, vol. 3, no. 1, pp. 69-85, Mar. 2002.
24. N. Gupta, "Remote sensing using hyperspectral and polarization images," in Proc. SPIE-Instrumentation for Air Pollution and Global Atmospheric Monitoring, J. O. Jensen and R. L. Spellicy, Eds., Feb. 2002, vol. 4574, pp. 184-192.
25. F. A. Sadjadi and C. S. Chun, "Remote sensing using passive infrared Stokes parameters," Opt. Eng., vol. 43, no. 10, pp. 2283-2291, Oct. 2004.
26. A. Mahalanobis and F. Goudail, "Methods for automatic target recognition by use of electro-optic sensors: Introduction to the feature issue," Appl. Opt., vol. 43, no. 2, pp. 207-209, Feb. 2004.
27. D. Manolakis, M. Rossacci, J. Cipar et al., "Statistical characterizing of natural hyperspectral backgrouds using t-elliptically contoured distributions," in Proc. SPIE-Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI, Jun. 2005, vol. 5806, pp. 56-65.
28. J. R. Schott, Remote Sensing: Image Chain Approach. New York: Cambridge Univ. Press, ch. 1, pp. 13-17.
29. B. W. Silverman, Density Estimation for Statistics and Data Analysis. London, U. K.: Chapman & Hall, ch. 5, p. 101.
30. S. Lim, K. Sohn, and C. Lee, "Principal component analysis for compression of hyperspectral images," in Proc. IGARSS, Jul. 2001, vol. 1, pp. 97-99.
31. L.-J. Cheng and G. Reys, "AOTF polarimetric hyperspectral imaging for mine detection," Proc. SPIE, vol. 2496, pp. 305-311.
32. H. Shingu, H. Kurosakib, K. Hommaa et al., "Earth observation system incorporating an LCTF spectropolarimeter," in Proc. SPIE-Sensors, Systems, and Next-Generation Satellites VI, 2003, vol. 4881, pp. 503-510.
33. N. Gupta, L. Denes, M. Gottlieb, D. Suhre et al., "Spectropolarimetric imaging using a field-portable imager," in Proc. SPIE-Imaging Spectrometry VI, 2000, vol. 4132, pp. 372-381.
34. Y.-Q. Zhao, Q. Pan, and H.-C. Zhang, "Fuse spectropolarimetric imagery by D-S reasoning," in Proc. SPIE-Polarization: Measurement, Analysis, and Remote Sensing VII, 2006, vol. 6240, p. 624 008-8.
35. K. Homma, M. Shibayama, H. Yamamotoa et al., "Water pollution monitoring using a hyperspectral imaging spectropolarimeter," in Proc. SPIE-Multispectral and Hyperspectral Remote Sensing Instruments and Applications II, 2005, vol. 5655, pp. 419-426.