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  1. 1. AN OVERVIEW OF RECENT ADVANCES IN POLARIMETRIC SAR INFORMATION EXTRACTION: ALGORITHMS AND APPLICATIONS IGARSS 2010 - Hawaii July 25 - July 30 Jong-Sen Lee*, Thomas Ainsworth Naval Research laboratory Washington DC 20375, USA
  2. 2. Introduction <ul><li>PolSAR information extraction technology has reached a certain degree of maturity. </li></ul><ul><li>New PolSAR satellites: </li></ul><ul><ul><li>ALOS/PALSAR – L-band </li></ul></ul><ul><ul><li>RADARSAT-2 – C-band </li></ul></ul><ul><ul><li>TERRASAR-X – X-band </li></ul></ul><ul><li>PolSAR textbooks (English): </li></ul><ul><ul><ul><li>2010, Cloude, Polarisation: applications in remote sensing . </li></ul></ul></ul><ul><ul><ul><li>2009, Lee and Pottier, Polarimetric Radar Imaging: from basic to applications . </li></ul></ul></ul><ul><ul><ul><li>2008, Massonnet, and Souyris, Imaging with Synthetic Aperture Radar . </li></ul></ul></ul><ul><ul><ul><li>2007, Mott, Remote Sensing with Polarimetric Radar . </li></ul></ul></ul><ul><li>Golden age in developing PolSAR applications. </li></ul>
  3. 3. ALOS – PALSAR . (Launched in January 2006) Repeat cycle 46 days (Tomakomai, Japan) 20 m x 20 m resolution
  4. 4. TerraSAR – X . Launched in June 15, 2007 Dual - Pol (HH,VV), (HH,HV), (VH,VV) Quad-Pol (Experimental) Repeat cycle: 11 days 3 meter resolution
  5. 5. RADARSAT-2 (RS2) <ul><li>C-Band Fine Quad-Pol Mode (8 m x 8 m resolution) </li></ul>. <ul><li>Launched in </li></ul><ul><li>December 14 2007 </li></ul><ul><li>24 days revisit cycle </li></ul>
  6. 6. Topics to be covered <ul><li>Review Advances in PolSAR information extraction for the last five years (TGRS, IGARSS). </li></ul><ul><ul><li>A) Target Decompositions/Orientation Angles, </li></ul></ul><ul><ul><li>B) Classification/Segmentation/Texture, </li></ul></ul><ul><ul><li>C) Calibration/Faraday Rotation </li></ul></ul><ul><ul><li>D) Speckle Filtering/Statistics, </li></ul></ul><ul><ul><li>E) Compact Polarimetry. </li></ul></ul><ul><ul><li>F) High-resolution PolSAR </li></ul></ul><ul><ul><li>G) Others: Forest / Vegetation, Ocean, surface parameters, bistatic, wetland, hard targets </li></ul></ul><ul><li>Not covered: </li></ul><ul><ul><li>Pol-InSAR </li></ul></ul><ul><ul><li>Polarimetric GPR </li></ul></ul>
  7. 7. <ul><li>Target Decompositions (Orientation Angles) </li></ul>
  8. 8. H Original (4-look) 5x5 9x9 H / A /   VERSUS MULTI-LOOKING A
  9. 9. Multi-look Effect on H/A/  <ul><li>Cloude/ Pottier Decomposition </li></ul><ul><ul><li>Multi-look effect on </li></ul></ul><ul><ul><li>Lopez-Martinez (2005), Lee (2008) </li></ul></ul><ul><ul><ul><li>Entropy is underestimated, Anisotropy overestimated </li></ul></ul></ul><ul><ul><ul><li>Bias removal </li></ul></ul></ul>
  10. 10. Cloude/ Pottier Decomposition <ul><ul><li>Alternative H and  without eigenvalue and eigenvector computation (Praks, 2009) </li></ul></ul><ul><ul><li>Applications: </li></ul></ul><ul><ul><ul><li>Forest (Garestier, 2009),P-band anisotropy related to forest height) </li></ul></ul></ul><ul><ul><ul><li>Oil Slick (Miliaccio, 2009), SIR-C, C-band </li></ul></ul></ul>
  11. 11. Freeman/Durden Decomposition <ul><li>FDD 3-component scattering model based decomposition </li></ul><ul><ul><ul><li>Issues: 1. More unknowns than equations </li></ul></ul></ul><ul><ul><li> 2. Reflection symmetry assumption </li></ul></ul><ul><ul><li> 3. Negative power </li></ul></ul><ul><li>Two-component decomposition from forest (Freeman, 2007) </li></ul><ul><ul><li>Volume + (Surface or Double bounce) – 5 unknowns, 5 equation </li></ul></ul>Surface Double bounce Volume Volume (Canopy) Double Bounce Rough Surface
  12. 12. Freeman/Durden Decomposition <ul><li>4-component scattering model (Yamaguchi, 2005) </li></ul>Surface Double bounce Volume Helix <ul><li>T 13 is not accounted for. (Lee, 2009) </li></ul><ul><ul><li>5-component scattering model decomposition? </li></ul></ul><ul><li>Negative Power issue: </li></ul><ul><ul><li>Orientation compensation reduces HV, that reduce negative power pixels (Lee, 2009, An, 2009,) </li></ul></ul><ul><ul><li>New volume scattering model (Yamaguchi, 2005) </li></ul></ul><ul><ul><li>New scacttering models and non-negative eigenvalues (van Zyl and Arii, 2009, 2010) </li></ul></ul>
  13. 13. Touzi Decomposition (Touzi, 2007) Cloude/Pottier: Symmetric Target Touzi Pauli Basis: Kennaugh-Huynen For asymmetric target
  14. 14. <ul><li>Polarization Orientation Angles </li></ul>
  15. 15. Polarization Orientation Angle (POA) <ul><li>Orientation angle effect on PolSAR images: (Lee and Schuler, 1999) </li></ul><ul><ul><li>Topography can affect scattering mechanisms </li></ul></ul><ul><ul><ul><li>HV power increased for high azimuth slopped surface </li></ul></ul></ul><ul><ul><li>Building not aligned along the azimuth direction </li></ul></ul><ul><ul><ul><li>HV power increased </li></ul></ul></ul><ul><ul><li>Point targets and random scatterers </li></ul></ul><ul><li>POA compensation is necessary for applications. If not, </li></ul><ul><ul><li>High azimuthal slopped surface – forest </li></ul></ul><ul><ul><li>Buildings – forest </li></ul></ul><ul><li>Faraday rotation estimation by orientation angle (Kimura, 2008) </li></ul>
  16. 16. Urban (buildings) Orientation Effects Freeman Decomposition Orientation Angle <ul><ul><li>E-SAR </li></ul></ul><ul><ul><li>L-Band Dresden </li></ul></ul>
  17. 17. The Effect of Radar Frequency <ul><li>JPL AIRSAR Freiburg Forest, 15 June 1991 </li></ul>POLSAR Derived Orientation Angles BY Circular Co-Pol Algorithm P-Band P-Band Orientation Angles L-Band Orientation Angles |HH-VV|, |HV|+|VH|, |HH+VV|
  18. 18. Polarization Orientation Angle Camp Roberts, CA.
  19. 19. Polarization Orientation Angle (POA) FLIGHT PO angles from C-band DEM C-Band DEM L-Band PolSAR derived PO angle PO angles derived By L-Band PolSAR PO angles derived from DEM of C-Band interferometry JPL AIRSAR L-Band PolSAR |HH-VV|, |HV|+|VH|, | HH+VV|
  20. 20. POA Compensation – Coherency T (Lee,2010) Rotation about LOS POA Estimation by Circular Pol Compensated results: 1) (= ) rotational invariant 2) (= ) always decreasing to minimum 3) (= ) consistently increasing because of pan and are roll invariant J.S. Lee and T.L. Ainsworth, “The effect of orientation angle compensation on coherency matrix and model-based decompositions”, IEEE TGRS, IGARSS2009 special issue, (in press).
  21. 21. POA Compensation – Coherency T <ul><li>Compensated results: </li></ul><ul><li>4) (= ) rotational invariant </li></ul><ul><li>5) reduced to zero by PO compensation </li></ul><ul><li>6) Roll invariant </li></ul><ul><li>Apply FDD after POA compensation: </li></ul><ul><li>(Lee, 2009, An, 2009, Yamaguchi , IGARSS 2010 ) </li></ul><ul><li>Mitigating topography effect for PolSAR classification </li></ul><ul><li>( Ainsworth, IGARSS2010 ) </li></ul>
  22. 22. The POA Compensation on Diagonal Terms , Orientation angle map After Before
  23. 23. B) Classification/Segmentation/Texture
  24. 24. UNSUPERVISED CLASSIFIER ( FREEMAN D. + WISHART) |HH-VV|, |HV |, |HH+VV| 4 th Iteration (15 classes) J.S. Lee, M.R. Grunes, E. Pottier, L. Ferro-Famil, “Unsupervised terrain classification preserving scattering characteristics,” IEEE Transactions on Geoscience and Remote Sensing,vol. 42, no.4, pp. 722-731, April, 2004.
  25. 25. DLR E-SAR L-Band Data Freeman Decomposition Classification Map Experimental Results – Oberphaffenhofen
  26. 26. Classification/Segmentation/Texture <ul><li>High-resolution PolSAR data makes Circular Gaussian or Wishart distributions seemingly insufficient for areas, such as, forest - Texture. (Ersahin, 2010, Lardeux, 2009, Doulgeris, 2008, Jager, 2007, Morio, 2007, Frery, 2007) </li></ul><ul><li>Classification : Assign a class for each pixel </li></ul><ul><li>Segmentation : Partitioning the whole scene into regions of same attributes (homogeneous areas). </li></ul><ul><li>Texture model: The product model (For example, K-distribution) </li></ul><ul><ul><li>SLC </li></ul></ul><ul><ul><li>Multi-look </li></ul></ul><ul><ul><li>g is the texture parameter, and can have many different pdfs. </li></ul></ul><ul><li>Issues: </li></ul><ul><ul><li>All three polarizations have the same distribution – frequently invalid </li></ul></ul><ul><ul><li>Multi-look reduce the texture effect. </li></ul></ul>
  27. 27. Classification/Segmentation/Texture <ul><li>Wavelet texture model –(de Grandi, 2007) </li></ul><ul><li>Support Vector Machine: find a hyper plane to separate the training sets containing many polarimetric parameters (Lardex, 2009) </li></ul><ul><li>Minimizing Stochastical Complexity: partition the image by polygons of MSC (Mario, 2007) </li></ul><ul><li>Fuzzy H/alpha unsupervised classifier (Sang-Eun, 2007, Kersten, 2005). </li></ul>
  28. 28. Classification/Segmentation/Texture <ul><li>Issues involving evaluation of classification accuracy. </li></ul><ul><ul><li>Ground truth map – inhomogeneous training areas </li></ul></ul><ul><ul><li>For example, Urban, Park, Ocean, Mountain - improper for classification evaluation </li></ul></ul><ul><ul><li>Planting map for crop class.? </li></ul></ul><ul><li>Advantage of multi-frequency </li></ul><ul><li>Wishart classifier remains </li></ul><ul><ul><li>optimal for ‘homogeneous’ areas </li></ul></ul><ul><ul><li>(Lardex, 2009) </li></ul></ul>
  29. 29. C) Calibration/ Faraday Rotation
  30. 30. Calibration/ Faraday Rotation <ul><li>PolSAR calibration to compensate for Faraday rotation (Kimura 2009, Takeshiro 2009, Jehle 2009, Meyer 2008, Freeman ) </li></ul><ul><li>ALOS/PALSAR, L-band are subject to ionospheric Faraday rotation. </li></ul><ul><li>Faraday rotation estimation algorithms: </li></ul><ul><ul><li>Circular right-left and left-right correlation (Meyer 2008) </li></ul></ul><ul><ul><li>Based on orientation angle of buildings (Kimura 2009) </li></ul></ul><ul><li>PALSAR calibration (Touzi, 2009) </li></ul><ul><li>Orientation angle perserving calibration (Ainsworth 2006) </li></ul>
  31. 31. Faraday Rotation <ul><ul><li>Circular right-left and left-right correlation </li></ul></ul>ALOS PALSAR, Gakona, Alaska Pauli Faraday rotation
  32. 32. D) Speckle Filtering/ PolSAR Statistics
  33. 33. PolSAR Speckle Filtering <ul><li>Speckle reduction is necessary for classification, segmentation, target decomposition (H/A/  ), image analysis, etc. </li></ul><ul><li>“ PolSAR Speckle Filtering” also known as </li></ul><ul><ul><li>“ Coherency Matrix Estimation” </li></ul></ul><ul><ul><li>“ Polarimetric Parameter Estimation” ( Vasil, IGARSS2010 ) </li></ul></ul><ul><li>Basic principle: Preserve scattering characteristics (coherency or covariance matrix) </li></ul><ul><ul><li>Select neighboring pixels of the same scattering property </li></ul></ul><ul><ul><li>Filter each element of the matrix equally and independently </li></ul></ul><ul><ul><ul><li>Different opinion (Lopez-Martinez, 2008, Foucher and Lopez-Martinez, IGARSS2010 ) </li></ul></ul></ul><ul><ul><ul><ul><li>Increase correlations of off-diagonal elements – wavelet </li></ul></ul></ul></ul>
  34. 34. PolSAR Speckle Filtering <ul><li>Intensity-Driven Adaptive Neighborhood - region grow (Vasile, 2006) </li></ul><ul><ul><li>Bias due to applying sigma filter </li></ul></ul><ul><li>Speckle filtering based on classification map </li></ul><ul><ul><li>Preserving scattering mechanism (Lee, 2006) </li></ul></ul><ul><li>Improved sigma filter (Lee 2008) </li></ul><ul><ul><li>Filter distributed target by </li></ul></ul><ul><ul><li>an improved sigma filter – no bias </li></ul></ul><ul><ul><li>Preserving point (high-return) targets in HH+VV, HH-VV and HV </li></ul></ul><ul><li>zc > 98 percentile z98 </li></ul><ul><li>Number of z98 pixels ≥ 5 in a 3x3 window </li></ul>X X X X X
  35. 35. Improved Sigma Filter |HH-VV|, |HV|, |HH+VV| Original 5x5 Sigma Filtered (Lee, IGARSS2008)
  36. 36. PolSAR Speckle Filtering/ PolSAR Statistics <ul><li>Speckle filtering is not an exact science. The filtering requirements depend on </li></ul><ul><ul><li>Applications </li></ul></ul><ul><ul><li>Personal preference </li></ul></ul><ul><li>Comparison of PolSAR filters </li></ul><ul><ul><li>Foucher et al (IGARSS2009) </li></ul></ul><ul><li>PolSAR Statistics </li></ul><ul><ul><li>Correlation term has the combination of multiplicative and additive noise depending on coherence – extension to multi-look data (Lopes-Martinez, 2007) </li></ul></ul><ul><ul><li>PDF for normalized coherency matrix (Vasile, 2010) </li></ul></ul>
  37. 37. E) Compact Polarimetry
  38. 38. Compact Polarimetry <ul><li>Alternative Dual-Pol SAR system: Transmitting a single polarization (  /4, circular) and receiving two orthogonal polarizations (H and V, CR and CL). Additional assumptions required for pseudo quad-pol reconstruction. </li></ul><ul><ul><li>Reduce pulse repetition frequency – double swath width </li></ul></ul><ul><ul><li>Simplify SAR system </li></ul></ul><ul><li>The  /4 mode (Souyris, 2005) named it “compact polarimetry” </li></ul><ul><ul><li>Transmit at 45  polarization and receiving (H,V) </li></ul></ul><ul><li>Modes:  /4 , CR transmit dual Circular Receiving , CR transmit (H,V) Receiving (Souyris, Stacy, Nord, Dubois-Fernandez, Raney) </li></ul>
  39. 39. Compact Polarimetry <ul><li>Consensus: Transmit Circular and receiving (H, V) </li></ul><ul><ul><ul><li>Transmit circular and receive (CR, CL) for ionosphere </li></ul></ul></ul><ul><li>Pseudo quad-pol reconstruction </li></ul><ul><ul><li>Reflection symmetry assumption </li></ul></ul><ul><ul><li>Additional identity is required </li></ul></ul><ul><ul><ul><li>Souyris, 2005 </li></ul></ul></ul><ul><ul><ul><li>Nord and Ainsworth, 2009 </li></ul></ul></ul>
  40. 40. Compact Polarimetry <ul><li>Incomplete polarimetric measurements </li></ul><ul><ul><li>CP measures only 4 parameters </li></ul></ul><ul><ul><li>Quad-pol measures 9 parameters </li></ul></ul><ul><li>Reconstruction is unreliable </li></ul><ul><ul><li>|HV| reconstruction </li></ul></ul><ul><ul><li>Polarization orientation angle can not be measured, especially for distributed targets </li></ul></ul><ul><ul><li>Target decompositions: H/A/  , Model-based decompositions </li></ul></ul><ul><li>Hardware issues of transmitting perfect circular pol </li></ul><ul><li>Summary: Compact polarimetry does not replace quad-pol in acquiring polarimetric information. </li></ul><ul><li>( Boerner, IGARSS2010 ) </li></ul>
  41. 41. F) High Resolution PolSAR
  42. 42. FSAR – “Future” Airborne SAR X-Band, PolSAR 2-Look, 0.5 m resolution , VV , HV , HH Images courtesy of Dr. Andreas Reigber, DLR, Germany
  43. 44. FSAR S-Band
  44. 45. Partial References <ul><li>A) Target Decompositions, Orientation Angles </li></ul><ul><li>[1] Wentao An,  Yi Cui,  Jian Yang, “ Three-Component Model-Based Decomposition for Polarimetric SAR Data ,” IEEE TGRS , vol.48, June 2010. </li></ul><ul><li>[2] Ballester-Berman, J.D.,  Lopez-Sanchez, J.M., “ Applying the Freeman–Durden Decomposition Concept to Polarimetric SAR Interferometry ,” IEEE TGRS , January 2010. </li></ul><ul><li>[3] Touzi, R.,  Deschamps, A.,  Rother, G., “ Phase of Target Scattering for Wetland Characterization Using Polarimetric C-Band SAR ,” IEEE TGRS , vol. 47, September 2009. </li></ul><ul><li>[4] Praks, J.,  Koeniguer, E.C.,  Hallikainen, M.T., “ Alternatives to Target Entropy and Alpha Angle in SAR Polarimetry ,” IEEE TGRS , vol. 47, July 2009. </li></ul><ul><li>[5] Lee, J.S., Ainsworth, T.L.,  Kelly, J.P.,  Lopez-Martinez, C., “ Evaluation and Bias Removal of Multilook Effect on Entropy/Alpha/Anisotropy in Polarimetric SAR Decomposition ,” IEEE TGRS , vol. 46, October 2008. </li></ul><ul><li>[6] Yajima, Y.,  Yamaguchi, Y.,  Sato, R.,  Yamada, H.,  Boerner, W.-M, “ POLSAR Image Analysis of Wetlands Using a Modified Four-Component Scattering Power Decomposition ,” IEEE TGRS , vol.46, June 2008. </li></ul><ul><li>[7] Freeman, A., “ Fitting a Two-Component Scattering Model to Polarimetric SAR Data from Forests ,” IEEE TGRS , vol. 45, August 2007. </li></ul><ul><li>[8] Touzi, R., “ Target Scattering Decomposition in Terms of Roll-Invariant Target Parameters ,” IEEE TGRS , vol. 45, January 2007. </li></ul><ul><li>[9] Cameron, W.L.,  Rais, H., “ Conservative Polarimetric Scatterers and Their Role in Incorrect Extensions of the Cameron Decomposition ,” IEEE TGRS , vol. 44, December 2006. </li></ul><ul><li>[10] Lopez-Martinez, C., Pottier, E.,  Cloude, S.R., “ Statistical Assessment of Eigenvector-Based Target Decomposition Theorems in Radar Polarimetry ,” IEEE TGRS , vol. 43, September 2005. </li></ul><ul><li>[11] Yamaguchi, Y.,  Moriyama, T.,  Ishido, M.,  Yamada, H., “ Four-component scattering model for polarimetric SAR image decomposition ,” IEEE TGRS , vol. 43, August 2005. </li></ul><ul><li>[12] Iribe, K.,  Sato, M., “ Analysis of Polarization Orientation Angle Shifts by Artificial Structures ,” IEEE TGRS , vol.45, November 2007 </li></ul><ul><li>[13] Marino, A., Cloude, S.R.,  Woodhouse, I.H., “ A Polarimetric Target Detector Using the Huynen Fork ,” IEEE TGRS , vol.48, May 2010. </li></ul><ul><li>[14] M. Arii, J.J. van Zyl, Y. Kim, “Adaptive decomposition of polarimetric SAR covariance matrix,” presented at IGARSS’2009, Cape Town, South Africa, July 2009. </li></ul><ul><li>[15] Lee, J.-S., Thomas L. Ainsworth, Kun-Shan Chen, “The effect of orientation angle compensation on polarimetric target decompositions,” Proceedings of IGARSS’2009 , Cape Town, South Africa, July 2009. </li></ul>
  45. 46. Partial References <ul><li>B. Classification/Segmentation/ Texture </li></ul><ul><li>[1] Ersahin, K.,  Cumming, I.G.,  Ward, R.K, “ Segmentation and Classification of Polarimetric SAR Data Using Spectral Graph Partitioning ,” IEEE TGRS , vol. 47, January 2010 </li></ul><ul><li>[2] Lardeux, C.,  Frison, P.-L., Tison, C.,  Souyris, J.-C.,  Stoll, B.,  Fruneau, B.,  Rudant, J.-P, “ Support Vector Machine for Multifrequency SAR Polarimetric Data Classification ,” IEEE TGRS vol.47, December 2009. </li></ul><ul><li>[3] Doulgeris, A.P.,  Anfinsen, S.N.,  Eltoft, T., “ Classification with a Non-Gaussian Model for PolSAR Data ,” IEEE TGRS , vol.46, October 2008. </li></ul><ul><li>[4] De Grandi, G.D., Lee, J.S., Schuler, D.L, “ Target Detection and Texture Segmentation in Polarimetric SAR Images Using a Wavelet Frame: Theoretical Aspects ,” IEEE TGRS , vol.45, November 2007. </li></ul><ul><li>[5] Jager, M., Neumann, M.,  Guillaso, S.,  Reigber, A., “ A Self-Initializing PolInSAR Classifier Using Interferometric Phase Differences ,” IEEE TGRS , vol.45, November 2007. </li></ul><ul><li>[6] Morio, J.,  Goudail, F.,  Dupuis, X.,  Dubois-Fernandez, P.C.,  Refregier, P., “ Polarimetric and Interferometric SAR Image Partition Into Statistically Homogeneous Regions Based on the Minimization of the Stochastic Complexity ,” IEEE TGRS , vol.45, November 2007. </li></ul><ul><li>[7] Frery, A.C.,  Correia, A.H.,  da Freitas, C.D., “ Classifying Multifrequency Fully Polarimetric Imagery With Multiple Sources of Statistical Evidence and Contextual Information ,” IEEE TGRS , vol.45, October 2007 </li></ul><ul><li>C. Calibration and Faraday Rotation </li></ul><ul><li>[1] Kimura, H., “ Calibration of Polarimetric PALSAR Imagery Affected by Faraday Rotation Using Polarization Orientation ,” IEEE TGRS vol.48, December 2009 </li></ul><ul><li>[2] Touzi, R.,  Shimada, M., “ Polarimetric PALSAR Calibration ,” IEEE TGRS, vol.48, December 2009 </li></ul><ul><li>[3] Takeshiro, A.,  Furuya, T.,  Fukuchi, H.,  “ Verification of Polarimetric Calibration Method Including Faraday Rotation Compensation Using PALSAR Data ,” IEEE TGRS, vol.47, December 2009 </li></ul><ul><li>[4] Jehle, M.,  Ruegg, M.,  Zuberbuhler, L.,  Small, D.,  Meier, E., “ Measurement of Ionospheric Faraday Rotation in Simulated and Real Spaceborne SAR Data ,” IEEE TGRS , vol. 47, May 2009. </li></ul><ul><li>[5] Meyer, F.J.,  Nicoll, J.B., “ Prediction, Detection, and Correction of Faraday Rotation in Full-Polarimetric L-Band SAR Data ,” IEEE TGRS , vol. 46, October 2008. </li></ul><ul><li>[6] Ren-Yuan Qi,  Ya-Qiu Jin, “ Analysis of the Effects of Faraday Rotation on Spaceborne Polarimetric SAR Observations at P-Band ,” IEEE TGRS , vol. 45, may 2007. </li></ul><ul><li>[7] Ainsworth, T.L.,  Ferro-Famil, L.,  Jong-Sen Lee, “ Orientation angle preserving a posteriori polarimetric SAR calibration ,” IEEE TGRS , vol . 44, April 2006. </li></ul>
  46. 47. Partial References <ul><li>D. Speckle Filtering and PolSAR Statistics </li></ul><ul><li>[1] Vasile, G.,  Ovarlez, J.-P.,  Pascal, F., Tison, C., “ Coherency Matrix Estimation of Heterogeneous Clutter in High-Resolution Polarimetric SAR Images ,” IEEE TGRS , vol.48, April 2010. </li></ul><ul><li>[2] Lopez-Martinez, C.,  Fabregas, X., “ Model-Based Polarimetric SAR Speckle Filter ,” IEEE TGRS , November 2008. </li></ul><ul><li>[3] Lopez-Martinez, C.,  Pottier, E., “ On the Extension of Multidimensional Speckle Noise Model From Single-Look to Multilook SAR Imagery ,” IEEE TGRS , February 2007. </li></ul><ul><li>[4] Vasile, G.,  Trouve, E.,  Jong-Sen Lee,  Buzuloiu, V., “ Intensity-driven adaptive-neighborhood technique for polarimetric and interferometric SAR parameters estimation ,” IEEE TGRS , vol. 44, June 2006. </li></ul><ul><li>[5] Jong-Sen Lee, Grunes, M.R.,  Schuler, D.L.,  Pottier, E.,  Ferro-Famil, L., “ Scattering-model-based speckle filtering of polarimetric SAR data ,” IEEE TGRS , vol. 44, January 2006. </li></ul><ul><li>[6] S. Foucher, C. Lopez-Martinez, G. Farage,  “An Evaluation of PolSAR Speckle Filters,”   Proceedings of IGARSS’2009 , Cape Town, South Africa, July 2009. </li></ul><ul><li>[9] Lee, JS, T.L. Ainsworth, K.S. Chen, “ Speckle filtering of dual-pol and polarimetric SAR data based on improved sigma filter ,” Proceedings of IGARSS2008, Boston, USA, 2008. </li></ul><ul><li>E. Compact Polarimetry </li></ul><ul><li>[1] Nord, M.E.,  Ainsworth, T.L.,  Jong-Sen Lee,  Stacy, N., “ Comparison of Compact Polarimetric Synthetic Aperture Radar Modes ,” IEEE TGRS , February 2009. </li></ul><ul><li>[2] Dubois-Fernandez, P.C.,  Souyris, J.-C.,  Angelliaume, S.,  Garestier, F., “ The Compact Polarimetry Alternative for Spaceborne SAR at Low Frequency ,” IEEE TGRS , Vol. 46, October 2008. </li></ul><ul><li>[3] Raney, R.K. “ Hybrid-Polarity SAR Architecture ,” IEEE TGRS , vol. 45, November 2007. </li></ul><ul><li>[4] Souyris, J.-C.,  et al. , “ Compact polarimetry based on symmetry properties of geophysical media: the π/4 mode ,” IEEE TGRS , vol. 43, March 2005. </li></ul>
  47. 48. Partial References <ul><li>F. Forest/Vegetation </li></ul><ul><li>[1] Neumann, M.,  Ferro-Famil, L.,  Reigber, A., “ Estimation of Forest Structure, Ground, and Canopy Layer Characteristics From Multibaseline Polarimetric Interferometric SAR Data ,” IEEE TGRS , vol. 48, March 2010. </li></ul><ul><li>[2] Garestier, F.,  Dubois-Fernandez, P.C.,  Guyon, D.,  Le Toan, T., “ Forest Biophysical Parameter Estimation Using L- and P-Band Polarimetric SAR Data ,” IEEE TGRS , vol. 47, October 2009. </li></ul><ul><li>[3] Haipeng Wang, Ouchi, K., “A ccuracy of the K-Distribution Regression Model for Forest Biomass Estimation by High-Resolution Polarimetric SAR: Comparison of Model Estimation and Field Data ,” IEEE TGRS , vol. 46, April 2008. </li></ul><ul><li>[4] Watanabe, M., et al., “ Forest Structure Dependency of the Relation between L-Band and Biophysical Parameters ,” IEEE TGRS , vol. 44, November 2006. </li></ul><ul><li>[5] Lopez-Sanchez, J.M.,  et al.,  “ Indoor wide-band polarimetric measurements on maize plants: a study of the differential extinction coefficient ,” IEEE TGRS , vol. 44, April 2006. </li></ul><ul><li>[6] McNeill, S.,  Pairman, D., “ Stand age retrieval in production forest stands in New Zealand using C- and L-band polarimetric Radar ,” IEEE TGRS , vol.43, November 2005. </li></ul><ul><li>G. Ocean Applications, Ship and Sea Ice Detection </li></ul><ul><li>[1] Migliaccio, M.,  Gambardella, A.,  Nunziata, F.,  Shimada, M.,  Isoguchi, O., “ The PALSAR Polarimetric Mode for Sea Oil Slick Observation ,” IEEE TGRS vol.47, December 2009 </li></ul><ul><li>[2] Margarit, G.,  Mallorqui, J.J.,  Fortuny-Guasch, J.,  Lopez-Martinez, C., “ Exploitation of Ship Scattering in Polarimetric SAR for an Improved Classification Under High Clutter Conditions ,” IEEE TGRS , April, 2009 </li></ul><ul><li>[3] Migliaccio, M.,  Gambardella, A.,  Tranfaglia, M., “ SAR Polarimetry to Observe Oil Spills ,” IEEE TGRS , vol. 45, February 2007. </li></ul><ul><li>[4] Margarit, G.,  Mallorqui, J.J.,  Rius, J.M.,  Sanz-Marcos, J., “ On the Usage of GRECOSAR, an Orbital Polarimetric SAR Simulator of Complex Targets, to Vessel Classification Studies ,” IEEE TGRS , vol. 44, December 2006. </li></ul><ul><li>[5] Nakamura, K.,  Wakabayashi, H.  et al., “ Observation of sea-ice thickness in the sea of Okhotsk by using dual-frequency and fully polarimetric airborne SAR (pi-SAR) data ,” IEEE TGRS , vol. 43, November 2005. </li></ul>
  48. 49. Partial References <ul><li>H. Surface Parameter Estimation </li></ul><ul><li>[1] Yunjin Kim,  van Zyl, J.J, “ A Time-Series Approach to Estimate Soil Moisture Using Polarimetric Radar Data ,” IEEE TGRS , August 2009. </li></ul><ul><li>[2] Sang-Eun Park,  Moon, W.M.  Duk-jin Kim, “ Estimation of Surface Roughness Parameter in Intertidal Mudflat Using Airborne Polarimetric SAR Data ,” IEEE TGRS , vol. 47, May 2009 </li></ul><ul><li>[3] Hajnsek, I.,  Jagdhuber, T.,  Schon, H.,  Papathanassiou, K.P., “ Potential of Estimating Soil Moisture Under Vegetation Cover by Means of PolSAR ,” IEEE TGRS vol. 47, February 2009. </li></ul><ul><li>I. Bistatic PolSAR </li></ul><ul><li>[1] Titin-Schnaider, C., “ Physical Meaning of Bistatic Polarimetric Parameters ,” IEEE TGRS , vol.48, May 2010. </li></ul><ul><li>[2] Feng Xu, Ya-Qiu Jin, “ Imaging Simulation of Bistatic Synthetic Aperture Radar and Its Polarimetric Analysis ,” IEEE TGRS , vol. 46, August 2008. </li></ul><ul><li>[3] Titin-Schnaider, C., “ Polarimetric Characterization of Bistatic Coherent Mechanisms ,” IEEE TGRS , vol. 46, May 2008. </li></ul><ul><li>[4] Souyris, J.-C.,  Tison, C., “ Polarimetric Analysis of Bistatic SAR Images From Polar Decomposition: A Quaternion Approach ,” IEEE TGRS , Vol. 45, September 2007. </li></ul><ul><li>J. Target Detection and Analysis </li></ul><ul><li>[1] Margarit, G.,  Mallorqui, J.J.,  Pipia, L., “ Polarimetric Characterization and Temporal Stability Analysis of Urban Target Scattering .” IEEE TGRS , vol. 48, April, 2010 </li></ul><ul><li>[2] Marquart, N.P.,  Molinet, F.,  Pottier, E.,  “ Investigations on the polarimetric behavior of a target near the soil ,” IEEE TGRS , vol.44, October 2006. </li></ul><ul><li>K. Other Applications </li></ul><ul><li>[1] Suwa, K.  Iwamoto, M., “ A Two-Dimensional Bandwidth Extrapolation Technique for Polarimetric Synthetic Aperture Radar Images ,” IEEE TGRS , vol.45, January 2007. </li></ul><ul><li>[2] Schneider, R.Z.  Papathanassiou, K.P.  Hajnsek, I.  Moreira, A., “ Polarimetric and interferometric characterization of coherent scatterers in urban areas ,” IEEE TGRS , Vol. 44, April 2006. </li></ul>
  49. 50. Partial References <ul><li>K. Other Applications </li></ul><ul><li>[1] Suwa, K.  Iwamoto, M., “ A Two-Dimensional Bandwidth Extrapolation Technique for Polarimetric Synthetic Aperture Radar Images ,” IEEE TGRS , vol.45, January 2007. </li></ul><ul><li>[2] Schneider, R.Z.  Papathanassiou, K.P.  Hajnsek, I.  Moreira, A., “ Polarimetric and interferometric characterization of coherent scatterers in urban areas ,” IEEE TGRS , Vol. 44, April 2006. </li></ul><ul><li>L. PolSAR Textbooks (in English) </li></ul><ul><li>[1] Cloude, S.R., Polarisation: applications in remote sensing , Oxford University Press, Oxford, New York, 2010. </li></ul><ul><li>[2] Lee, J.S. and Pottier, E., Polarimetric Radar Imaging: from basic to applications , Taylor & Francis/CRC Press, Boca Raton, London, New York, 2009. </li></ul><ul><li>[3] Massonnet, D. and Souyris, J-C, Imaging with Synthetic Aperture Radar , , Taylor & Francis/CRC Press, Boca Raton, London, New York, 2008. </li></ul><ul><li>[4] Mott, H., Remote Sensing with Polarimetric Radar , Wiley & Sons, New Jersey, 2007. </li></ul>
  50. 51. Conclusion <ul><li>PolSAR information extraction research has reach a certain degree of maturity. </li></ul><ul><li>The availability of space borne and airborne PolSAR data will stimulate applications and developing advanced information extraction algorithms. </li></ul><ul><li>TanDEM-X Mission: Bistatic PolSAR research </li></ul><ul><li>High resolution (less than 1 m) PolSAR will open up new area of research and applications. </li></ul><ul><li>ALOS/PALSAR, and RADARSAT-2 follow ups, and TerraSAR-L </li></ul><ul><li>PolSAR research has a bright future </li></ul>