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Edge Detection in Polarimetric SAR Image based on Bandelet Transform

by Roy Thankachan, Sethunadh R., Ameer P. M.
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 45
Year of Publication: 2019
Authors: Roy Thankachan, Sethunadh R., Ameer P. M.
10.5120/ijca2019918587

Roy Thankachan, Sethunadh R., Ameer P. M. . Edge Detection in Polarimetric SAR Image based on Bandelet Transform. International Journal of Computer Applications. 181, 45 ( Mar 2019), 33-38. DOI=10.5120/ijca2019918587

@article{ 10.5120/ijca2019918587,
author = { Roy Thankachan, Sethunadh R., Ameer P. M. },
title = { Edge Detection in Polarimetric SAR Image based on Bandelet Transform },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2019 },
volume = { 181 },
number = { 45 },
month = { Mar },
year = { 2019 },
issn = { 0975-8887 },
pages = { 33-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number45/30424-2019918587/ },
doi = { 10.5120/ijca2019918587 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:09:12.847823+05:30
%A Roy Thankachan
%A Sethunadh R.
%A Ameer P. M.
%T Edge Detection in Polarimetric SAR Image based on Bandelet Transform
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 45
%P 33-38
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Polarimetric Synthetic Aperture Radar is being used widely in order to extract the features of target image including civilian and military applications. Edge detection in PolSAR images is highly challenging task due to the occurrence of speckle noise in these images although widely used for the strategic applications. This paper presents a multi-resolution edge detection method for PolSAR images using the bandelet transform. Bandelet transform can provide flexible multiscale and directional decomposition of images including SAR images. Edge enhancement of the input image is done after decomposing it using bandelet transform and the resultant bandelet coefficients are modified through the maximisation of the polarimetric contrast between the adjacent subbands using Lagrangian methods. Taking advantage of the directional features of bandelet transform an algorithm is developed for retaining the geometrical features of images such as edges, boundaries etc present in SAR images while ensuring effective speckle noise removal. Here the geometrical features in images are enhanced in the bandelet domain by fusing the different directional subband coefficients at different scales. The performance of this method is verified using real PolSAR images. The result shows that proposed scheme eliminates speckle noise and retrieved edges are continuous and complete.

References
  1. J. Sen Lee and E.Pottier, “Overview of Polarimetric Radar Imaging,” in Polarimetric Radar Imaging From Basics to Applications, New York: CRC Press., 2013, pp. 2-28.
  2. R. Touzi, A. Lopès, and P. Bousquet, “A statistical and geometrical edge detector for SAR images,” IEEE Trans. Geosci. Remote Sens., vol. 26,no. 6, pp. 764–773, Nov. 1988.
  3. C. J. Oliver, D. Blacknell, and R. G. White, “Optimum edge detection in SAR,” Proc. Inst. Elect. Eng., vol. 143, no. 1, pp. 31–40, Feb. 1996.
  4. M. T. Alonso, C. Lopez-Martinez, J. J. Mallorqui, and P. Salembier, “Edge enhancement algorithm based on the wavelet transform for automatic edge detection in SAR images,” IEEE Trans. Geosci. Remote Sens.,vol. 49, no. 1, pp. 222–235, Jan. 2011.
  5. G. Y. Zhou, Y. Cui, Y. L. Chen, J. Yang, and H. F. Rashvand, “SAR image edge detection using curvelet transform and Duda operator,” Electron. Lett., vol. 46, no. 2, pp. 167–169, Jan. 2009.
  6. S. Yi, D. Labate, G. R. Easley, and H. Krim, “A shearlet approach to edge analysis and detection,” IEEE Trans. Image Process., vol. 18, no. 5, pp. 929–941, May 2009.
  7. Q.W. Li, G. Y. Huo, H. Li, G. C. Ma, and A. Y. Shi, “Bionic vision-based synthetic aperture radar image edge detection method in nonsubsampled contourlet transform domain,” IET Radar, Sonar Navigat., vol. 6, no. 6, pp. 526–535, Jul. 2012.
  8. J. Schou, H. Skriver, A. A. Nielsen, and K. Conradsen, “CFAR edge detector for polarimetric SAR images,” IEEE Trans. Geosci. Remote Sens., vol. 41, no. 1, pp. 20–32, Jan. 2003.
  9. G. Y. Zhou et al., “Linear feature detection in polarimetric SAR images,” IEEE Trans. Geosci. Remote Sens., vol. 49, no. 4, pp. 1453–1463, Apr. 2011.
  10. R. J. Jin, J. J. Yin, W. Zhou, and J. Yang, “Edge detection in polarimetric SAR images based on the nonsubsampled contourlet transform,” in Proc.IEEE Radar Con., May 2015, pp.0319-0323
  11. J.Rujin and Junjun Yin, “Improved multiscale edge detection method for polarimetric SAR images”, IEEE Trans. Geosci. Remote Sens., vol. 13, no.8,pp. 1104-1108, Aug. 2016
  12. N. Raj, R.Sethunadh and P.R. Aparna,” Object detection in SAR image based on bandelet transform”, J. Vis. Commun. Image R. vol. 40, pp. 376-383, 2016
  13. W.Wang, D. Xiang et al "Enhanced edge detection for polarimetric SAR images using a directional span-driven adaptive window", Int. Journal of Remote Sensing, 2018
  14. J. Sen Lee and E.Pottier, “Electromagnetic Vector Scattering Operators,” in Polarimetric Radar Imaging From Basics to Applications, New York: CRC Press. 2013, pp. 53-72.
  15. J. Sen Lee and E.Pottier, “Polarimetric SAR Speckle Filtering,” in Polarimetric Radar Imaging From Basics to Applications, New York: CRC Press., 2013, pp. 143-147.
  16. M.Jansen, M. Malfait and A. Bultheel, “Generalized cross validation for wavelet thresholding”, IEEE Trans. Signal Process., vol. 56 no.1, pp. 33-44, 1997
  17. S. Al Zubi, N. Islam and M. Abbod, “ Multiresolution analysis using wavelet, ridgelet and curvelet transforms for medical image segmentation,” Int. J. of Biomedical Imaging, vol. 2011
  18. Niedermeier, A., E. Romaneessen, and S. Lehner. “Detection of Coastlines in SAR Images Using Wavelet Methods.” IEEE Transactions on Geoscience and Remote Sensing vol.38 (5): pp. 2270–2281, 2000
  19. Nascimento, A. D. C., M. M. Horta, A. C. Frery, and R. J. Cintra. “Comparing Edge Detection Methods Based on Stochastic Entropies and Distances for PolSAR Imagery.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing .vol.7 (2), pp. 648–663. 2014
  20. D.Xiang, Y.Ban, W.Wang,T.Tang and Y. Su, "Edge Detector for Polarimetric SAR Images Using SIRV Model and Gauss-Shaped Filter," IEEE Trans. Geosci. Remote Sens., vol.13, no.11 pp. 1661-1665,Nov. 2016.
  21. B. Liu, Z. Zhang, X. Liu, and W. Yu, "Edge extraction for polarimetric SAR images using degenerate filter with weighted maximum likelihood estimation," IEEE Trans. Geosci. Remote Sens., vol. 11, no.12 pp. 2140-2144, Dec. 2014.
  22. E. Le Pennec and S.Mallat, “Sparse geometric image representation with bandelets”, IEEE Trans. Image Process., vol. 14, no.4, pp. 423-438, Apr. 2005
  23. G. Peyre and S.Mallat, “Orthogonal bandelet bases for geometric images approximation,” Commun. Pure and Appl. Math., vol.000, pp. 0001-0029, 2000
Index Terms

Computer Science
Information Sciences

Keywords

PolSAR bandelet speckle directional subbands

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