Skip to main content

SAR Imagery and Applications

  • Chapter
  • 1013 Accesses

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

3-6 References

  • Besag, J. (1974), “Spatial interaction and the statistical analysis of lattice systems (with discussion)”, Journal of Royal Statistical Society, series B, 36(2): 192–326.

    MATH  MathSciNet  Google Scholar 

  • Besag, J. (1986), “On the statistic analysis of dirty pictures”, Journal of Royal Statistical Society, series B, 48(3): 259–302.

    MATH  MathSciNet  Google Scholar 

  • Bruzzone, L. and D.F. Prieto (2000), “Automatic analysis of the difference image for unsupervised change detection”, IEEE Transactions on Geoscience and Remote Sensing, 38(3): 1171–1182.

    Article  Google Scholar 

  • Castleman, K.R. (1996), Digital Image Processing, New York: Printice Hall.

    Google Scholar 

  • China Integrative Atlas (1990), Beijing: China Map Publishing Company, 151.

    Google Scholar 

  • Cloude, S.R. (1986), “Group theory and polarization algebra”, Optik, 75(1): 26–36.

    Google Scholar 

  • Cloude, S.R. and E. Pottier (1996), “A review of target decomposition theorems in radar polarimetry”, IEEE Transactions on Geoscience and Remote Sensing, 34(2): 498–518.

    Article  Google Scholar 

  • Cloude, S.R. and E. Pottier (1997), “An entropy based classification scheme for land application of polarimetric SAR”, IEEE Transactions on Geoscience and Remote Sensing, 35(1): 68–78.

    Article  Google Scholar 

  • Cloude, S.R. (1999), “Wide-band polarimetric radar inversion studies for vegetation layers,” IEEE Transactions on Geoscience and Remote Sensing, 37(5): 2430–2441.

    Article  Google Scholar 

  • Cloude, S.R., K.P. Papathanassiou and E. Pottier (2001), “Radar polarimetry and polarimetric interferometry”, IEICE Transactions on Electronics, E84-C(12): 1814–1822.

    Google Scholar 

  • Copeland, A.C., G. Ravichandran and M.M. Trivedi (1995), “Localized Radon transform-based detection of ship wakes in SAR images”, IEEE Transactions on Geoscience and Remote Sensing, 33(1): 35–45.

    Article  Google Scholar 

  • Demmel, J. (1997), Applied Numerical Linear Algebra, Society for Industrial and Applied Mathematics.

    Google Scholar 

  • Dempster, A.P., N.M. Laird and D.B. Rubin (1977), “Maximum linkelihood from incomplete data via the EM algorithm”, Journal of Royal Statistical Society, 39(1): 1–38.

    MATH  MathSciNet  Google Scholar 

  • Eldhuset, K. (1996), “An automatic ship and ship wake detection system for spaceborne SAR images in coastal region”, IEEE Transactions on Geoscience and Remote Sensing, 34(4): 1010–1019

    Article  Google Scholar 

  • Chan, F.H.Y., F.K. Lam and H. Zhu (1998), “Adaptive thresholding by variational method”, IEEE Transaction on Geoscience Remote Sensing, 7(3): 468–473.

    Google Scholar 

  • Freeman, A. and S.L. Durden (1998), “A three-component scattering model for polarimetric SAR data”, IEEE Transactions on Geoscience and Remote Sensing, 36(3): 963–973.

    Article  Google Scholar 

  • Fukunaga, K. (1990), Introduction to Statistical Pattern Recognition, 2nd ed. London: Academic.

    MATH  Google Scholar 

  • Fung, A.K. (1994), “Microwave scattering and emission models and their applications,” Boston: Artech House.

    Google Scholar 

  • Ghiglia, D.C. and L.A. Romero (1994), “Robust two-dimensional weighted and unweighted phase unwrapping that uses fast transforms and iterative methods”, Journal of Optical Society of American A, 11(1): 107–117.

    Google Scholar 

  • Hennings, R. et al. (1999), “Radar imaging of Kelvin arms of ship wakes”, International Journal of Remote Sensing, 20(13): 2519–2543

    Article  Google Scholar 

  • Hovanessian, S.A. (1980), Introduction to Synthetic Array and Imaging Radars, Mass: Artech House.

    Google Scholar 

  • Huynen, J.R. (1970), “Phenomenological Theory of Radar Targets”, PhD. thesis, University of Technology, Delft, Netherlands.

    Google Scholar 

  • Itoh, T., H. Sueda and T. Wantanabe (1996), “Motion compensation for ISAR via centroid tracking”, IEEE Transactions on Aerospace and Electronic Systems, 32(3): 1191–1197.

    Article  Google Scholar 

  • Jin, Y.Q. (1994), Electromagnetic Scattering Modeling for Quantitative Remote Sensing, Singapore: World Scientific.

    Google Scholar 

  • Jin, Y.Q. and S.R. Cloude (1994), “Numerical eigenanalysis of the coherency matrix for a layer of random nonspherical scatterers”, IEEE Transactions on Geoscience and Remote Sensing, 32(6): 1179–1185.

    Article  Google Scholar 

  • Jin, Y.Q. (2000), Information of Electromagnetic Scattering and Radiative Transfer in Natural Media, Beijing: Science Press.

    Google Scholar 

  • Jin, Y.Q. and S. Wang (2001), “An algorithm for ship detection from SAR image using the radon transform and topographical image processing”, The Imaging Science Journal, 48(4): 159–163.

    Google Scholar 

  • Jin, Y.Q. and Z. Li (2002), “Numerical simulation for radar surveillance of a ship target in oceanic clutters”, Chinese Science Bulletin, 47(21): 1766–1771.

    Article  Google Scholar 

  • Jin, Y.Q. and Y. Chen (2002), “An improved method of the minimum entropy for refocusing moving target image in the SAR observation”, The Imaging Science Journal, 50(6): 147–152.

    Google Scholar 

  • Jin, Y.Q. and L. Luo (2004), “Terrain topographic inversion from single-pass polarimetric SAR image data by using polarimetric stokes parameters and morphological algorithm”, Science in China, (F), 47(4): 490–500.

    Article  MathSciNet  MATH  Google Scholar 

  • Jin, Y.Q., F. Chen and L. Luo (2004), “Automatic analysis of change detection of multi-temporal ERS-2 SAR images by using two-thresholds EM and MRF algorithms”, The Imaging Science Journal, 52: 234–241.

    Article  Google Scholar 

  • Kasetkasem, T. and P. Varshney (2002), “An image change detection algorithm based on Markov random field model”, IEEE Transactions on Geoscience and Remote Sensing, 40(8): 1815–1823.

    Article  Google Scholar 

  • Kasilingam, D. et al. (2000), “Focusing of synthetic aperture radar images of moving targets using minimum entropy adaptive filters”, International Geoscience and Remote Sensing Symposium (IGARSS’00): 74–76.

    Google Scholar 

  • Kong, J.A. et al. (1990), “Classification of earth terrain using polarimetric synthetic aperture radar images”, PIER (Progress in Electromagnetic Research), ed. by J. A. Kong, New York: Elsevier, 3(6).

    Google Scholar 

  • Lee, J.S., R.W. Jansen and D.L. Schuler (1998), “Polarimetric analysis and modeling of multi-frequency SAR signatures from gulf stream fronts”, IEEE Journal of Oceanic Engineering, 23(4): 322–333.

    Article  Google Scholar 

  • Lee, J.S. et al. (1999), “Unsupervised classification using polarimetric decomposition and the complex Wishart classifier”, IEEE Transactions on Geoscience and Remote Sensing, 37(5): 2249–2258.

    Article  Google Scholar 

  • Lee, J.S., D.L. Schuler and T.L. Answorth (2000), “Polarimetric SAR data compression for terrain azimuthal slope variation”, IEEE Transaction on Geoscience Remote Sensing, 38(5): 2153–2163.

    Article  Google Scholar 

  • Lee, J.S. et al. (2004), “Unsupervised terrain classification preserving polarimetric scattering characteristics,” IEEE Transactions on Geoscience and Remote Sensing, 42(4): 722–731.

    Article  Google Scholar 

  • Li, X. et al. (2000), “Auto-focusing of ISAR images based on entropy minimization”, IEEE Transactions on Aerospace and Electronic System, 35(4): 1240–1251.

    Article  Google Scholar 

  • Lin, I.I. et al. (1996), “Ship and ship wake detection in the ERS SAR imagery using computer-based algorithm”, International Geoscience and Remote Sensing Symposium (IGARSS’96): 151–153

    Google Scholar 

  • Ridd, M.K. and J.J. Liu (1998), “A comparison of four algorithms for change detection in an urban environment”, Remote Sensing of Environment, 63(2), 95–100.

    Article  Google Scholar 

  • Moon, T.K. (1996), “The expectation-maximization algorithm”, Signal Processing Magazine, 13(6): 47–60.

    Article  Google Scholar 

  • Oliver, C. and S. Quegan (1998), Understanding Synthetic Aperture RadarImages, Mass: Artech House.

    Google Scholar 

  • Plummer, S. E., and P. J. Curran (1998), “BOREAS RSS-04 1994 Jack pine leaf biochemistry and modeled spectra in the SSA, data set”, Available on-line [http://www.daac.ornl.gov] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A.

    Google Scholar 

  • Pritt, M.D. and J.S. Shipman (1994), “Least-squares two-dimensional phase unwrapping using FFT’s”, IEEE Transaction on Geoscience Remote Sensing, 32(3): 706–708.

    Article  Google Scholar 

  • Pritt, M.D. (1996), “Phase unwrapping by means of multi-grid techniques for interferometric SAR”, IEEE Transactions on Geoscience Remote Sensing, 34(3): 728–738.

    Article  Google Scholar 

  • Render, A.P. and H.F. Walker (1984), “Mixture densities maximum likelihood and the EM algorithm”, SIAM Review, 26(2): 195–239.

    Article  MathSciNet  Google Scholar 

  • Rey, M.T. et al. (1990), “Application of Radon transform techniques to wake detection in Seasat-A SAR images”, IEEE Transactions on Geoscience and Remote Sensing, 28(4): 553–560

    Article  Google Scholar 

  • Rignot, E.J.M. and J.J. Van Zyl (1993), “Change detection techniques for ERS-1 SAR data”, IEEE Transactions on Geoscience and Remote Sensing, 31(4): 896–906.

    Article  Google Scholar 

  • Schuler, D.L., J.S. Lee, T.L. Answorth and M.R. Grunes (2000), “Terrain topography measurements using multipass polarimetric synthetic aperture radar data”, Radio Science, 35: 813–832.

    Article  Google Scholar 

  • Schuler, D.L., T.L. Answorth and J.S. Lee (1998), “Topographic mapping using polarimetric SAR data”, International Journal of Remote Sensing, 19(1): 141–160.

    Article  Google Scholar 

  • Shahshahani, B.M. and D.A. Landgrebe (1994), “The effect of unlabeled samples in reducing the small size problem and mitigating the Hughes phenomenon”, IEEE Transactions on Geoscience and Remote Sensing, 32(5): 1087–1095.

    Article  Google Scholar 

  • Singh, A. (1989), “Digital change detection techniques using remotely-sensed data”, International Journal of Remote Sensing, 10(6): 989–1003.

    Google Scholar 

  • Takajo, H. and T. Takahashi (1998), “Least-squares phase estimation from phase difference”, Journal of Optical Society of American (A), 5: 416–425.

    Article  Google Scholar 

  • Ulaby, F.T. et al. (1986), “Textural information in SAR images”, IEEE Transactions on Geoscience and Remote Sensing, 20(2): 35–45.

    Google Scholar 

  • Van Zyl, J.J. (1989), “Unsupervised classification of scattering behavior using radar polarimetry data”, IEEE Transactions on Geoscience and Remote Sensing, 27(1): 36–45.

    Article  Google Scholar 

  • Wahl, D.E. et al. (1994), “Phase gradient auto-focusing — A robust tool for high resolution SAR phase correction”. IEEE Transactions on Aerospace and Electronic Systems, 30(3): 827–835.

    Article  Google Scholar 

  • Ward, K.D. and S. Watts (1985), “Radar sea clutter”, Microwave Journal, 28(6): 109–121

    Google Scholar 

  • Werness, S. et al. (1990), “Moving target imaging algorithm for SAR data”. IEEE Transactions on Aerospace and Electronic Systems, 21(1): 57–67.

    Article  Google Scholar 

  • Xu, F. and Y.Q. Jin (2005), “Deorientation theory of polarimetric scattering targets and application of terrain surface classification”, IEEE Transactions on Geoscience and Remote Sensing 43(10):1–16.

    Article  MATH  Google Scholar 

  • Zebker, H.A. et al. (1991), “Calibrated imaging radar Polarimetry: Techniques examples and applications”, IEEE Transactions on Geoscience and Remote Sensing, 29(6): 942–961.

    Article  Google Scholar 

  • Zhang, Q. et al. (2002), “Urban built-up land change detection with road density and spectral information from multi-temporal Landsat TM data”, International Journal of Remote Sensing, 23(15): 3057–3078.

    Article  Google Scholar 

Download references

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer

About this chapter

Cite this chapter

(2006). SAR Imagery and Applications. In: Theory and Approach of Information Retrievals from Electromagnetic Scattering and Remote Sensing. Springer, Dordrecht. https://doi.org/10.1007/1-4020-4030-X_3

Download citation

  • DOI: https://doi.org/10.1007/1-4020-4030-X_3

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-4029-0

  • Online ISBN: 978-1-4020-4030-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics