Polarimetric SAR Image Filtering by Infinite Number of Looks Prediction Technique
Speckle filtering in synthetic aperture radar (SAR) and polarimetric SAR (PolSAR) images is indispensable before the extraction of the useful information. The minimum mean square error estimate of the filtered pixels conducted to the definition of a linear rule between the values of the filtered pix...
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| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , , |
| التنسيق: | article |
| منشور في: |
2021
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://hdl.handle.net/11073/23905 |
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| _version_ | 1864513442454437888 |
|---|---|
| author | Yahia, Mohamed |
| author2 | Ali, Tarig Mortula, Maruf Abdelfattah, Riadh Elmahdy, Samy |
| author2_role | author author author author |
| author_facet | Yahia, Mohamed Ali, Tarig Mortula, Maruf Abdelfattah, Riadh Elmahdy, Samy |
| author_role | author |
| dc.creator.none.fl_str_mv | Yahia, Mohamed Ali, Tarig Mortula, Maruf Abdelfattah, Riadh Elmahdy, Samy |
| dc.date.none.fl_str_mv | 2021 2022-06-06T09:38:52Z 2022-06-06T09:38:52Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | M. Yahia, T. Ali, M. M. Mortula, R. Abdelfattah and S. Elmahdy, "Polarimetric SAR Image Filtering by Infinite Number of Looks Prediction Technique," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 4167-4184, 2021, doi: 10.1109/JSTARS.2021.3070421. 2151-1535 http://hdl.handle.net/11073/23905 10.1109/JSTARS.2021.3070421 |
| dc.language.none.fl_str_mv | en_US |
| dc.publisher.none.fl_str_mv | IEEE |
| dc.relation.none.fl_str_mv | https://doi.org/10.1109/JSTARS.2021.3070421 |
| dc.subject.none.fl_str_mv | Linear regression Minimum mean square error (MMSE) filter Polarimetric synthetic aperture radar (PoLSAR) Speckle filtering |
| dc.title.none.fl_str_mv | Polarimetric SAR Image Filtering by Infinite Number of Looks Prediction Technique |
| dc.type.none.fl_str_mv | Peer-Reviewed Published version info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | Speckle filtering in synthetic aperture radar (SAR) and polarimetric SAR (PolSAR) images is indispensable before the extraction of the useful information. The minimum mean square error estimate of the filtered pixels conducted to the definition of a linear rule between the values of the filtered pixels and their variances. Hence, the filtered pixel for infinite number of looks (INL) is predicted by a linear regression of means and variances for various window sizes. In this article, the infinite number of looks prediction (INLP) filter is explored in details to emphasize its ability to reduce speckle and preserve the spatial details. Then, the linear regression rule has been adapted to PolSAR context in order to preserve the polarimetric information. The number of the processed pixels used in the linear regression is adjusted to the variability of the scene. This effort increased the filtering performances. The reduction of the correlation between the pixels which constitutes an additional filtering criterion is discussed. Compared to the initially applied filter, the results showed that the improved INLP filter increased in speckle reduction level, augmented the preservation of the spatial details, increased the spatial resolution, reduced the correlation between the pixels and better preserved the polarimetric information. Simulated, one-look and multilook real PolSAR data were used for validation. |
| format | article |
| id | aus_5eb3c7150b7e7ba653c3e9f775e7328c |
| identifier_str_mv | M. Yahia, T. Ali, M. M. Mortula, R. Abdelfattah and S. Elmahdy, "Polarimetric SAR Image Filtering by Infinite Number of Looks Prediction Technique," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 4167-4184, 2021, doi: 10.1109/JSTARS.2021.3070421. 2151-1535 10.1109/JSTARS.2021.3070421 |
| language_invalid_str_mv | en_US |
| network_acronym_str | aus |
| network_name_str | aus |
| oai_identifier_str | oai:repository.aus.edu:11073/23905 |
| publishDate | 2021 |
| publisher.none.fl_str_mv | IEEE |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Polarimetric SAR Image Filtering by Infinite Number of Looks Prediction TechniqueYahia, MohamedAli, TarigMortula, MarufAbdelfattah, RiadhElmahdy, SamyLinear regressionMinimum mean square error (MMSE) filterPolarimetric synthetic aperture radar (PoLSAR)Speckle filteringSpeckle filtering in synthetic aperture radar (SAR) and polarimetric SAR (PolSAR) images is indispensable before the extraction of the useful information. The minimum mean square error estimate of the filtered pixels conducted to the definition of a linear rule between the values of the filtered pixels and their variances. Hence, the filtered pixel for infinite number of looks (INL) is predicted by a linear regression of means and variances for various window sizes. In this article, the infinite number of looks prediction (INLP) filter is explored in details to emphasize its ability to reduce speckle and preserve the spatial details. Then, the linear regression rule has been adapted to PolSAR context in order to preserve the polarimetric information. The number of the processed pixels used in the linear regression is adjusted to the variability of the scene. This effort increased the filtering performances. The reduction of the correlation between the pixels which constitutes an additional filtering criterion is discussed. Compared to the initially applied filter, the results showed that the improved INLP filter increased in speckle reduction level, augmented the preservation of the spatial details, increased the spatial resolution, reduced the correlation between the pixels and better preserved the polarimetric information. Simulated, one-look and multilook real PolSAR data were used for validation.American University of SharjahSmart City Research InstituteIEEE2022-06-06T09:38:52Z2022-06-06T09:38:52Z2021Peer-ReviewedPublished versioninfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfM. Yahia, T. Ali, M. M. Mortula, R. Abdelfattah and S. Elmahdy, "Polarimetric SAR Image Filtering by Infinite Number of Looks Prediction Technique," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 4167-4184, 2021, doi: 10.1109/JSTARS.2021.3070421.2151-1535http://hdl.handle.net/11073/2390510.1109/JSTARS.2021.3070421en_UShttps://doi.org/10.1109/JSTARS.2021.3070421oai:repository.aus.edu:11073/239052024-08-22T12:06:50Z |
| spellingShingle | Polarimetric SAR Image Filtering by Infinite Number of Looks Prediction Technique Yahia, Mohamed Linear regression Minimum mean square error (MMSE) filter Polarimetric synthetic aperture radar (PoLSAR) Speckle filtering |
| status_str | publishedVersion |
| title | Polarimetric SAR Image Filtering by Infinite Number of Looks Prediction Technique |
| title_full | Polarimetric SAR Image Filtering by Infinite Number of Looks Prediction Technique |
| title_fullStr | Polarimetric SAR Image Filtering by Infinite Number of Looks Prediction Technique |
| title_full_unstemmed | Polarimetric SAR Image Filtering by Infinite Number of Looks Prediction Technique |
| title_short | Polarimetric SAR Image Filtering by Infinite Number of Looks Prediction Technique |
| title_sort | Polarimetric SAR Image Filtering by Infinite Number of Looks Prediction Technique |
| topic | Linear regression Minimum mean square error (MMSE) filter Polarimetric synthetic aperture radar (PoLSAR) Speckle filtering |
| url | http://hdl.handle.net/11073/23905 |