Comparative Study of Adaptive Filters, Boxcar, and Goldstein in Radar Interferometry Using Envisat Satellite Images over the Yazd-Ardakan Plain
Subject Areas : Journal of Radar and Optical Remote Sensing and GIS
1 - Graduate Student remote sensing and geographical information system, Islamic Azad University, Yazd
Keywords: Adaptive, Boxcar, Goldestein, Interferogram, Interferometry, SAR Images,
Abstract :
Objective: This study aims to evaluate and identify the most effective speckle noise reduction filter for Synthetic Aperture Radar (SAR) images, specifically focusing on maintaining image clarity and preserving edge details.
Methods: SAR systems, which send microwave pulses to measure reflectors and distances, are prone to speckle noise due to the interference of reflected waves from heterogeneous surfaces. This noise negatively impacts image quality, complicating the extraction of accurate environmental data. The research utilized 1-Sentinel SAR images of the Yazd-Ardakan plain and applied various noise reduction filters to these images.
Results: The effectiveness of each filter was assessed based on its ability to reduce speckle noise while preserving critical features, particularly edges. Results indicated that the adaptive filter outperformed the other filters by maintaining sharp edges and reducing noise, making it the most suitable option for this type of image enhancement. The Goldstein filter, while effective in removing noise, compromised phase accuracy, and the Boxcar filter blurred edges.
Conclusion: This study concludes that the adaptive filter is the best option for SAR image enhancement in the study area, offering significant potential for more accurate environmental monitoring. Further research is recommended to explore the combination of different filters for improved results in complex environments.
Ali, S. M., Javed, M. Y., Khattak, N. S., & Mohsin, A. (2008). Despeckling of synthetic aperture radar images using inner product spaces in undecimated wavelet domain. International Journal of Electronics and Communication Engineering, 2(1), 84-89.
Domg, Y., & Milne, A. K. (2001). Toward edge sharpening: a SAR speckle filtering algorithm. IEEE Transactions on Geoscience and Remote Sensing, 39(4), 851-863. https://doi.org/10.1109/36.917910
Falahatibagherabadi, M., & Amini, J. (2010). Investigation of de-speckling filters in SAR images for forest areas in the north of Iran. Mapping Engineering and Spatial Information, 4(1).
Forouzanfar, M., Abrishami-Moghaddam, H., & Dehghani, M. (2010). A new effective approach for enhancement of SAR images based on extraction of interscale dependencies in the wavelet domain. Scientific Quarterly Journal of Geosciences, 19(76), 17-22. https://doi.org/10.22071/gsj.2010.55636
Hanssen, R. F. (2001). Radar interferometry: data interpretation and error analysis (Vol. 2). Springer Science & Business Media.
Lee, J. S., & Pottier, E. (2017). Polarimetric radar imaging: from basics to applications. CRC press. https://doi.org/10.1201/9781420054989
Lillesand, T., Kiefer, R. W., & Chipman, J. (2015). Remote sensing and image interpretation. John Wiley & Sons.
Lopes, A., Nezry, E., Touzi, R., & Laur, H. (1990, May). Maximum a posteriori speckle filtering and first order texture models in SAR images. In 10th annual international symposium on geoscience and remote sensing (pp. 2409-2412). Ieee.
Maghsoodi, Y., & Mahdavi, S. (2016). Radar remote sensing basics (1st ed.). Tehran: Sharif Industrial University.
Maghsoudi, Y. (2011). Analysis of Radarsat-2 full polarimetric data for forest mapping.
Mirzadeh, S. M. J., Jin, S., Parizi, E., Chaussard, E., Bürgmann, R., Delgado Blasco, J. M., ... & Mirzadeh, S. H. (2021). Characterization of irreversible land subsidence in the Yazd‐Ardakan plain, Iran from 2003 to 2020 InSAR time series. Journal of Geophysical Research: Solid Earth, 126(11), e2021JB022258. https://doi.org/10.1029/2021JB022258
Oliver, C., & Quegan, S. (2004). Understanding synthetic aperture radar images. SciTech Publishing.
Panahi, H. (2017). ENVI 4.8 application guide with overlay on 10.1 ArcGIS. Yazd Azad University.
Saevarsson, B. B., Sveinsson, J. R., & Benediktsson, J. A. (2004, September). Combined wavelet and curvelet denoising of SAR images. In IGARSS 2004. 2004 IEEE International Geoscience and Remote Sensing Symposium (Vol. 6, pp. 4235-4238). IEEE. https://doi.org/10.1109/IGARSS.2004.1370070
Salahshouri, F., & Almodaresi, S. (2016). Selection of optimal filter for speckle noise reduction in radar images to extract coastline of Qeshm Island. National Geomatics.
Sedighi, M. (2017). Investigation of subsidence rate of Varamin plain using geodetic tools for accurate alignment data, GPS and radar images [Doctoral dissertation, Islamic Azad University of Shahrood].
Tso, B., & Mather, P. M. (2003). Classification methods for remotely sensed data (No. 9681). CRC Press.
Zarekamali, M., Alhoseini Almodaresi, S. A., & Naghdi, K. (2017). Comparing the magnitude of the earth’s vertical relocation using the SBAS algorithm in X and C radar bands (Case study: Tehran lands). Journal of RS and GIS for Natural Resources, 8(3), 104-120.
