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Tuesday, 26/07/2011, Vancouver, Canada, IGARSS 2011

INFLUENCE OF SPECKLE FILTERING OF POLARIMETRIC SAR DATA ON DIFFERENT CLASSIFICATION METHODS. Fang Cao 1 , Charles-Alban Deledalle 1 , Jean-Marie Nicolas 1 , Florence Tupin 1 , Loïc Denis 2 , Laurent Ferro-Famil 3 , Eric Pottier 3 , Carlos López-Martínez 4

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Tuesday, 26/07/2011, Vancouver, Canada, IGARSS 2011

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  1. INFLUENCE OF SPECKLE FILTERING OF POLARIMETRIC SAR DATA ON DIFFERENTCLASSIFICATION METHODS Fang Cao1, Charles-Alban Deledalle1, Jean-Marie Nicolas1, Florence Tupin1, Loïc Denis2, Laurent Ferro-Famil3, Eric Pottier3, Carlos López-Martínez4 1 Institut Télécom, Télécom ParisTech, France 2 Université de Lyon, France 3 Université de Rennes 1, France 4 Universitat Politècnica de Catalunya, Spain Tuesday, 26/07/2011, Vancouver, Canada, IGARSS 2011

  2. Index Index Introduction Speckle filtering Decomposition and classification Conclusion page 2

  3. Introduction Introduction • Speckle filtering: • A pre-processing step to reduce the speckle noise before image segmentation or classification Tested filters: Refined Lee’s filter, IDAN filter and NL-PolSAR filter • Decomposition and classification: • Evaluation of the performance of speckle filtering methods through Cloude–Pottier decomposition and Wishart H/alpha classification page 3

  4. Index Index Introduction Speckle filtering Decomposition and classification Conclusion page 4

  5. Speckle filtering approaches page 5

  6. Speckle filtering approaches page 6

  7. Speckle filtering approaches page 7

  8. Speckle filtering approaches page 8

  9. Speckle filtering approaches page 9

  10. Speckle filtering approaches Refined Lee IDAN NL-PolSAR |SHH- SVV| |SHV| |SHH+ SVV| San Francisco (JPL L-Band AIRSAR)

  11. Speckle filtering approaches Refined Lee IDAN NL-PolSAR |SHH- SVV| |SHV| |SHH+ SVV| Flevoland (JPL L-Band AIRSAR)

  12. Index Index Introduction Speckle filtering Decomposition and classification Conclusion page 12

  13. Cloude-Pottier Decomposition • Eigenvalue/eigenvector calculation of the coherency matrix of fully polarimetric SAR data. • Covering the whole range of scattering mechanisms • Automatically basis invariant. Coherency matrix: Hermitian, semi-definite positive matrix → diagonalization

  14. Cloude-Pottier Decomposition Probability of each 3 scattering mechanism Entropy H: the global distribution of scattering mechanism  angle: the type of scattering mechanism Anisotropy A : the two least important scattering mechanism effects

  15. 1.0 0 b Entropy Alpha Anisotropy 90° 0 1.0 0 Refined Lee IDAN NL-PolSAR San Francisco by JPL L–Band AIRSAR

  16. 1.0 0 b Entropy Alpha Anisotropy 90° 0 The refined Lee filter and the NLPolSAR filters have similar performance. The IDAN filter usually introduces bias in entropy and anisotropy values, which may result to unreliable classification results. 1.0 0 Refined Lee IDAN NL-PolSAR San Francisco by JPL L–Band AIRSAR

  17. The Wishart H  Classification Building Forest Water H/ initialization: 8 classes

  18. The Wishart H /  Classification Wishart clustering • Supervised algorithm • Based on the complex Wishart distribution of coherency matrix • Use maximum likelihood criterion Distance measure V : the cluster center coherency matrix : the trace of a matrix Maximum likelihood criterion

  19. Decomposition and classification Refined LEE NL-PolSAR AIRSAR ALOS/PALSAR Radarsat–2 page 19

  20. Decomposition and classification Refined LEE The results of AIRSAR, ALOS/PALSAR and RadarSat-2 data show that the classification results with different sensors are quite similar, except the water area in the AIRSAR data, which is due to the big variation of the incidence angle of the airborne sensor. NL-PolSAR AIRSAR ALOS/PALSAR Radarsat–2 page 20

  21. The NL-PolSAR filter has better performance than the refined Lee filter, for example, the golf course areas and the lakes in the AIRSAR classification results.

  22. Index Index Introduction Speckle filtering Decomposition and classification Conclusion page 22

  23. Conclusion • Comparison of 3 speckle filters: Refined Lee’s filter, IDAN filter and the NL-PolSAR filter • Comparison of the influence on decomposition and classification Cloude-Pottier decomposition & Wishart H/a classification • Obtained results with different sensors: Radarsat-2, ALOS/PALSAR and AIRSAR • The NL-PolSAR filter achieves the best performance in our experimental tests

  24. Thank you! page 24

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