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New Method for Ship Detection

Introducing a novel ship detection technique based on Generalized Optimization of Polarimetric Contrast Enhancement (GOPCE) for SAR images, achieving high accuracy with low false alarm rates.

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New Method for Ship Detection

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  1. New Method for Ship Detection Jian Yang Hongji Zhang Dept. of Electronic Eng., Tsinghua Univ. Yoshio Yamaguchi Dept. of Inform. Eng., Niigata Univ.

  2. Outline • Background • Polarization Entropy and Similarity Parameter • GOPCE based ship detection • Experiment Results • Summary

  3. 1. Background • Polarimetric Whitening Filter (PWF) • Novak, Burl • Identity Likelihood Ratio Test • DeGraff • HH HV VV RR LL Entropy Span • Touzi

  4. Touzi’s work

  5. Optimization of Polarimetric Contrast Enhancement (OPCE) Ioannidis Hammers Kostinski Boerner Yamaguchi Yang

  6. Problem • Can we employ the OPCE for ship detection? • It is easy to get the average Kennaugh matrix of sea clutter, but how can we get or construct the average Kennaugh matrix of ships? • Can we extend the OPCE for ship detection?

  7. 2 Polarization entropy and similarity parameters

  8. Approximate expression From the least square method and Vieta's Theorem The average error:

  9. The Formula has a good approximation to the theoretical value of the polarization entropy Eigenvalues and logarithm are unnecessary!!! Running Time by the proposed formula is only 5% of that by the traditional approach J. Yang, Y. Chen, Y. Peng, Y. Yamaguchi, H. Yamada, “New formula of the polarization entropy”, IEICE Trans. Commun., 2006, E89-B(3), 1033-1035

  10. Similarity parameter single-look case Multi-look case J. Yang, et al., “Similarity between two scattering matrices,” Electronics Letters, vol.37, no. 3, pp. 193-194, 2001.

  11. Similarity between a target and a plate: surface scattering Similarity between a target and a diplane: Double-bounce scattering

  12. Generalized OPCE (GOPCE) based ship detection J. Yang, Y. Yamaguchi, W. -M. Boerner, S. M. Lin, “Numerical methods for solving the optimal problem of contrast enhancement,” IEEE Trans. Geosci. Remote Sensing, 2000, 38(2), pp. 965-971

  13. GOPCE: Generalized OPCE J. Yang, et al., “Generalized optimization of polarimetric contrast enhancement”, IEEE GRSL., vol.1, no.3, pp.171-174, 2004

  14. GOPCE based ship detection For a sea area subject to:

  15. Average Kennaugh matrix of ships • the scattering contributions of a ship • direct reflection of plates • double reflections of diplates of the ship • some multi-reflections of the surface of the ship, or some multi-reflections between the ship and the sea surface

  16. Experimental results NASA/JPL AirSAR over Sydney coast, Australia. Span image

  17. Experiment results

  18. Experiment results Power Image by OPCE

  19. Experiment results GP Image by GOPCE

  20. Experiment results Filtered result by PWF

  21. Detection results: false alarm rate 1% span PWF OPCE GOPCE

  22. 5. Summary (1) OPCE has been developed (2) GOPCE is effective for ship detection

  23. Thank you! yangjian_ee@tsinghua.edu.cn

  24. Speckle Filtering Observation Point • Speckle phenomenon in SAR/POLSAR Surface Roughness Scattering from distributed scatterers Coherent interferences of waves scattered from many randomly distributed scatterers in the resolution cell Granular Noise Speckle Phenomenon

  25. Speckle Filtering • Challenge of speckle filtering Speckle Filtering Speckle Reduction Detail Preservation These two objectives should be achieved simultaneously

  26. Pre-test Approach for Speckle Filtering • Classical Methods for Speckle Filtering • Boxcar Filter • MMSE Lee’s filter with edge detector To-be-filtered pixel 3*3 boxcar Pixel selected for averaging 8-direction edge detectors

  27. Pre-test Approach for Speckle Filtering Summary of Speckle Filtering : Two-Step Methodology To-be-filtered pixel patch : pixel itself and its local neighboring Pre-tested pixels patch non-local area :other than neighboring area pre-test : selecting homogenous pixels in non-local area by patch An example of pre-testing homogenous pixels in non-local area by patch

  28. Pre-test Approach for Speckle Filtering • Non-local but homogeneous pixels using proposed method

  29. Pre-test Approach for Speckle Filtering • For each pixel - For each pixel in non-local searching area • 1. Calculate the similarity test between the patches with and • as the center respectivel • 2. If test > threshold, accept • as the homogenous pixel to , and calculate the weight • 3. Average homogenous pixels with their normalized weight to get filtered covariance matrix Calculate the similarity between 2 patches patch searching area of

  30. Pre-test Approach for Speckle Filtering SAR-Convair 580 C-band Image size : 340*220 Resolution : 6.4m*10m • Experimental Results • Original (b) Refined Lee (c) Pre-test

  31. C-band AirSAR data • SAN Francisco area • Original • Boxcar • Refined Lee • Pre-test • 4 multi-look • Image size : • 300*300 • Resolution : • About 10m*10m

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