Importance of Speckle Filter Window Size and its Impact on Speckle Reduction in SAR Images

Authors

  • Kiran Dasari Department of Electronics and Communication Engineering National Institute of Technology Warangal, Telangana, 506004, India
  • L. Anjaneyulu Department of Electronics and Communication Engineering National Institute of Technology Warangal, Telangana, 506004, India

Keywords:

SAR, ALOS PALSAR-2, Speckle Filtering, Filter Window Size, K-Mean Clustering

Abstract

The use of microwaves in remote sensing made a revolution in many fields such as space technology, agriculture, urban planning, disaster management, ocean studies. The advantages of the microwaves over optical are, they can penetrate through clouds, vegetation, soil, and day/night operation is possible by active sensing. SAR (Synthetic Aperture Radar) data set from Advanced Land Observing Satellite Phase Array L-band Synthetic Aperture Radar (ALOS PALSAR -2), of Mt Fuji, Japan, has been taken as a study area in this work. In this study, we explored the potential of window size on speckle filters, removal of speckle using speckle filters, the importance of speckle filtering for further classification. In this study, the dataset is evaluated by using different speckle filters like mean, median, frost, gamma map, and lee, for different speckle filter sizes 3X3, 5X5, 7X7, 9X9, and 11X11. This study specifies the selection of data in terms of filter size, polarization, and amplitude or intensity for an image. Speckle suppression indices are calculated on SAR data sets and the results are compared to various speckle filters. Based on SSI, ENL and SMPI values, Median Filter Intensity HH with filter size 7X7 is opted for further classification (K-Means Clustering).

Author Biographies

Kiran Dasari, Department of Electronics and Communication Engineering National Institute of Technology Warangal, Telangana, 506004, India

Kiran Dasari is currently pursuing his Ph.D. in the area of Microwave Remote Sening in the Department of Electronics and communication Engineering, National Institute of Technology Warangal. He received his M.Tech degree in Embedded Systems from the Department of Electronics and communication Engineering, Padmasri Dr. B. V. Raju Institute of Technology,Telangana, India in 2012, and B.Tech degree in Electonics and communication Engineering from Institute of Aerounatical Engineering, Telangana, India in 2010.He has 2 International Journals and 3 International Conference papers to his credit.

L. Anjaneyulu, Department of Electronics and Communication Engineering National Institute of Technology Warangal, Telangana, 506004, India

L. Anjaneyulu was born in 1967 in India. He obtained his B.Tech (ECE) in 1989, M.Tech in 1991 and Ph.D. in 2010 from N.I.T, Warangal, India. He worked as Project Officer at Institute of Armament Technology, Pune, India for 5 years from 1991 and involved in the design of Surface borne and Air-borne Radar systems for clutter measurement application. Later, he worked as Staff Scientist at Helios Systems, Madras, India for 2 years and engaged in the development of Radio Wave propagation assessment software modules for ship-borne radars. He has been with the department of Electronics and Communications Engineering at National Institute of Technology, Warangal, India since 1997. His areas of interest include Computer Networks, Electromagnetic Field Theory, Microwave & Radar Engineering, Microwave Remote Sensing and Neural Networks & Fuzzy Logic Systems. He has completed few defence R&D Projects and has 50 papers to his credit in National and International Conferences and journals. He is a Life member of ISTE and a member of IEEE, IEEE Antennas and Propagation Society, IEEE Signal Processing Society.

References

Jong-Sen Lee, Eric Poitter.: Polarimetric Radar Imaging from basics to applications, CRC Press, (2009).

Lillisand, Kiefer, and Chipman. : Remote Sensing and Image Interpretation, John Wiley & Sons, (2012).

D.Haldar, A. Das, S.Mohan, O.Pal, R. S. Hooda, M.Chakraborty, Assessment of L-Band SAR Data at Different Polarization Combinations for Crop and Other Land use

Classification, Progress In Electromagnetic Research, vol. 36, pp. 303-321, 2012.

Zhixin Qi, Anthony Gar-On Yeh, Xia Li, Zheng Lin.: A novel algorithm for land use and land cover classification using RADARSAT-2 polarimetric, Remote Sensing Environment, vol. 118, pp. 21-39, 2012.

Iain H. Woodhouse.: Introduction to Microwave Remote Sensing. CRC Press, (2006).

George Joseph.: Fundamentals of Remote Sensing, Universities Press, (2003).

Christopher R. Jackson: NOAA SAR Manual.

http://www.sarusersmanual.com.

http://www.sarusersmanual.com/ManualPDF/NOAASARManu

al_CH01_pg001-024.pdf.

J. W. Goodman, Some fundamental properties of speckle, Journal of Optical Society, vol. 66 , pp. 1145-1150, 1976.

Jong Sen Lee, A Simple Speckle Smoothing Algorithm for Synthetic Aperture Radar Images, IEEE Journals & Magazines, vol. 13, pp. 85-89, 1983.

Fang Qiu, Judith Berglund, R. John Jensen, Pathik Thakkar, and Dianwei Ren, Speckle Noise Reduction in SAR Imagery Using a Local Adaptive Median Filter, GIScience and Remote Sensing, vol. 41 , pp. 244-266, 2004.

Japan Aerospace Exploration Agency website. : http://www/global.jaxa.jp/.

ALOS-2/PALSAR-2 Level 1.1/1.5/2.1/3.1 CEOS SAR Product Format Description data sheet, Japan.

The ESA Polsarpro website: http://www/earth.eo.esa.int/polsarpro/faq.html /.

Exelis,http://www.exelisvis.com/ProductsServices/ENVIProducts/ENVISARscape.aspx

The HEXAGONGEOSPATIAL:http://www/hexagongeospatial.com/products/remote-sensing/erdasimagine/.

The Array systems computing Inc.:http://www.array.ca/about/corporate-overview/.

Argenti. F, Lapini. A, Bianchi. T, Alparone. L.: A Tutorial on Speckle Reduction in Synthetic Aperture Radar Images. IEEE Journals & Magazines, vol. 1, pp. 6-35, 2013.

Yongwei Sheng, Zong-Guo Xia. : A Comprehensive Evaluation of Filters for Radar Speckle Suppression. IEEE Conference Publications, 3 (1996), 1559-1561.

Shamsoddini. A, Tinder J.C, Image Texture Preservation in Speckle Noise Suppression. ISPRS TC VII Symposium, vol. 38, pp. 239-244, 2010.

J. S. Lee, M. R. Grunes, G. De Grandi, Polarimetric, SAR Speckle Filtering and Its Impact on Classification, Geo Science and Remote Sensing, vol. 2, pp. 1038-1042, 1997.

Dellepiane, and Elena Angiati,Quality Assessment of Despeckled SAR Images, IEEE Journal Of Selected Topics In Applied Earth Observations And Remote Sensing, Vol. 7,

pp.691-707, 2014.

Dasari Kiran, L. Anjaneyulu, P.V Jayasri, A.V.V.Prasad, Importance of Speckle Filtering in Image classification of SAR Data, Proc. ICMOCE, pp. 349-352, 2015.

Published

2020-10-22

How to Cite

Kiran Dasari, & L. Anjaneyulu. (2020). Importance of Speckle Filter Window Size and its Impact on Speckle Reduction in SAR Images . International Journal of Advances in Microwave Technology, 2(2), 98-102. Retrieved from https://ijamt.com/index.php/ijamt/article/view/50

Issue

Vol. 2 No. 2 (2017): Volume 2, Issue 2 (May 2017)

Section

Rasearch Paper