Despeckling of SAR Images Using BEMD-Based Adaptive Frost Filter
Abstract In image processing, removal of speckle noise from a satellite image is a challenging task for the researchers. There are various approaches for speckle noise reduction. Generally, the speckle noises are scattered, in satellite images, medical images and synthetic aperture radar (SAR) image...
Ausführliche Beschreibung
Autor*in: |
Painam, Ranjith Kumar [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2022 |
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Anmerkung: |
© Indian Society of Remote Sensing 2022 |
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Übergeordnetes Werk: |
Enthalten in: Journal of the Indian Society of Remote Sensing - Neu Delhi : Springer India, 2008, 51(2022), 9 vom: 24. Jan., Seite 1879-1890 |
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Übergeordnetes Werk: |
volume:51 ; year:2022 ; number:9 ; day:24 ; month:01 ; pages:1879-1890 |
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DOI / URN: |
10.1007/s12524-022-01495-x |
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Katalog-ID: |
SPR05356572X |
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520 | |a Abstract In image processing, removal of speckle noise from a satellite image is a challenging task for the researchers. There are various approaches for speckle noise reduction. Generally, the speckle noises are scattered, in satellite images, medical images and synthetic aperture radar (SAR) images. This paper introduces a bidimensional empirical mode decomposition (BEMD)-based adaptive filtering method for despeckling of SAR image. The noisy SAR image is decomposed into different bidimensional intrinsic mode function (BIMF) levels using BEMD and then filtering is performed on the first BIMF level, as it contains the high-frequency noise component. This adaptation process effectively filters out the noisy image component without destroying the original image component. A BEMD-based adaptive Frost filter is introduced in this paper for despeckling of SAR images. The despeckling performances of our proposed filtering method are further analyzed by visual evaluation and also using performance parameters comparatively. Our reconstructed images show better performance quantitatively and qualitatively compared to other filters. | ||
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650 | 4 | |a Synthetic aperture radar |7 (dpeaa)DE-He213 | |
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650 | 4 | |a Image reconstruction |7 (dpeaa)DE-He213 | |
700 | 1 | |a Suchetha, M. |4 aut | |
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10.1007/s12524-022-01495-x doi (DE-627)SPR05356572X (SPR)s12524-022-01495-x-e DE-627 ger DE-627 rakwb eng Painam, Ranjith Kumar verfasserin aut Despeckling of SAR Images Using BEMD-Based Adaptive Frost Filter 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Indian Society of Remote Sensing 2022 Abstract In image processing, removal of speckle noise from a satellite image is a challenging task for the researchers. There are various approaches for speckle noise reduction. Generally, the speckle noises are scattered, in satellite images, medical images and synthetic aperture radar (SAR) images. This paper introduces a bidimensional empirical mode decomposition (BEMD)-based adaptive filtering method for despeckling of SAR image. The noisy SAR image is decomposed into different bidimensional intrinsic mode function (BIMF) levels using BEMD and then filtering is performed on the first BIMF level, as it contains the high-frequency noise component. This adaptation process effectively filters out the noisy image component without destroying the original image component. A BEMD-based adaptive Frost filter is introduced in this paper for despeckling of SAR images. The despeckling performances of our proposed filtering method are further analyzed by visual evaluation and also using performance parameters comparatively. Our reconstructed images show better performance quantitatively and qualitatively compared to other filters. Adaptive filters (dpeaa)DE-He213 BEMD (dpeaa)DE-He213 Synthetic aperture radar (dpeaa)DE-He213 Speckle noise (dpeaa)DE-He213 Image reconstruction (dpeaa)DE-He213 Suchetha, M. aut Enthalten in Journal of the Indian Society of Remote Sensing Neu Delhi : Springer India, 2008 51(2022), 9 vom: 24. Jan., Seite 1879-1890 (DE-627)573088853 (DE-600)2439566-3 0974-3006 nnns volume:51 year:2022 number:9 day:24 month:01 pages:1879-1890 https://dx.doi.org/10.1007/s12524-022-01495-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 51 2022 9 24 01 1879-1890 |
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10.1007/s12524-022-01495-x doi (DE-627)SPR05356572X (SPR)s12524-022-01495-x-e DE-627 ger DE-627 rakwb eng Painam, Ranjith Kumar verfasserin aut Despeckling of SAR Images Using BEMD-Based Adaptive Frost Filter 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Indian Society of Remote Sensing 2022 Abstract In image processing, removal of speckle noise from a satellite image is a challenging task for the researchers. There are various approaches for speckle noise reduction. Generally, the speckle noises are scattered, in satellite images, medical images and synthetic aperture radar (SAR) images. This paper introduces a bidimensional empirical mode decomposition (BEMD)-based adaptive filtering method for despeckling of SAR image. The noisy SAR image is decomposed into different bidimensional intrinsic mode function (BIMF) levels using BEMD and then filtering is performed on the first BIMF level, as it contains the high-frequency noise component. This adaptation process effectively filters out the noisy image component without destroying the original image component. A BEMD-based adaptive Frost filter is introduced in this paper for despeckling of SAR images. The despeckling performances of our proposed filtering method are further analyzed by visual evaluation and also using performance parameters comparatively. Our reconstructed images show better performance quantitatively and qualitatively compared to other filters. Adaptive filters (dpeaa)DE-He213 BEMD (dpeaa)DE-He213 Synthetic aperture radar (dpeaa)DE-He213 Speckle noise (dpeaa)DE-He213 Image reconstruction (dpeaa)DE-He213 Suchetha, M. aut Enthalten in Journal of the Indian Society of Remote Sensing Neu Delhi : Springer India, 2008 51(2022), 9 vom: 24. Jan., Seite 1879-1890 (DE-627)573088853 (DE-600)2439566-3 0974-3006 nnns volume:51 year:2022 number:9 day:24 month:01 pages:1879-1890 https://dx.doi.org/10.1007/s12524-022-01495-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 51 2022 9 24 01 1879-1890 |
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10.1007/s12524-022-01495-x doi (DE-627)SPR05356572X (SPR)s12524-022-01495-x-e DE-627 ger DE-627 rakwb eng Painam, Ranjith Kumar verfasserin aut Despeckling of SAR Images Using BEMD-Based Adaptive Frost Filter 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Indian Society of Remote Sensing 2022 Abstract In image processing, removal of speckle noise from a satellite image is a challenging task for the researchers. There are various approaches for speckle noise reduction. Generally, the speckle noises are scattered, in satellite images, medical images and synthetic aperture radar (SAR) images. This paper introduces a bidimensional empirical mode decomposition (BEMD)-based adaptive filtering method for despeckling of SAR image. The noisy SAR image is decomposed into different bidimensional intrinsic mode function (BIMF) levels using BEMD and then filtering is performed on the first BIMF level, as it contains the high-frequency noise component. This adaptation process effectively filters out the noisy image component without destroying the original image component. A BEMD-based adaptive Frost filter is introduced in this paper for despeckling of SAR images. The despeckling performances of our proposed filtering method are further analyzed by visual evaluation and also using performance parameters comparatively. Our reconstructed images show better performance quantitatively and qualitatively compared to other filters. Adaptive filters (dpeaa)DE-He213 BEMD (dpeaa)DE-He213 Synthetic aperture radar (dpeaa)DE-He213 Speckle noise (dpeaa)DE-He213 Image reconstruction (dpeaa)DE-He213 Suchetha, M. aut Enthalten in Journal of the Indian Society of Remote Sensing Neu Delhi : Springer India, 2008 51(2022), 9 vom: 24. Jan., Seite 1879-1890 (DE-627)573088853 (DE-600)2439566-3 0974-3006 nnns volume:51 year:2022 number:9 day:24 month:01 pages:1879-1890 https://dx.doi.org/10.1007/s12524-022-01495-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 51 2022 9 24 01 1879-1890 |
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10.1007/s12524-022-01495-x doi (DE-627)SPR05356572X (SPR)s12524-022-01495-x-e DE-627 ger DE-627 rakwb eng Painam, Ranjith Kumar verfasserin aut Despeckling of SAR Images Using BEMD-Based Adaptive Frost Filter 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Indian Society of Remote Sensing 2022 Abstract In image processing, removal of speckle noise from a satellite image is a challenging task for the researchers. There are various approaches for speckle noise reduction. Generally, the speckle noises are scattered, in satellite images, medical images and synthetic aperture radar (SAR) images. This paper introduces a bidimensional empirical mode decomposition (BEMD)-based adaptive filtering method for despeckling of SAR image. The noisy SAR image is decomposed into different bidimensional intrinsic mode function (BIMF) levels using BEMD and then filtering is performed on the first BIMF level, as it contains the high-frequency noise component. This adaptation process effectively filters out the noisy image component without destroying the original image component. A BEMD-based adaptive Frost filter is introduced in this paper for despeckling of SAR images. The despeckling performances of our proposed filtering method are further analyzed by visual evaluation and also using performance parameters comparatively. Our reconstructed images show better performance quantitatively and qualitatively compared to other filters. Adaptive filters (dpeaa)DE-He213 BEMD (dpeaa)DE-He213 Synthetic aperture radar (dpeaa)DE-He213 Speckle noise (dpeaa)DE-He213 Image reconstruction (dpeaa)DE-He213 Suchetha, M. aut Enthalten in Journal of the Indian Society of Remote Sensing Neu Delhi : Springer India, 2008 51(2022), 9 vom: 24. Jan., Seite 1879-1890 (DE-627)573088853 (DE-600)2439566-3 0974-3006 nnns volume:51 year:2022 number:9 day:24 month:01 pages:1879-1890 https://dx.doi.org/10.1007/s12524-022-01495-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 51 2022 9 24 01 1879-1890 |
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10.1007/s12524-022-01495-x doi (DE-627)SPR05356572X (SPR)s12524-022-01495-x-e DE-627 ger DE-627 rakwb eng Painam, Ranjith Kumar verfasserin aut Despeckling of SAR Images Using BEMD-Based Adaptive Frost Filter 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Indian Society of Remote Sensing 2022 Abstract In image processing, removal of speckle noise from a satellite image is a challenging task for the researchers. There are various approaches for speckle noise reduction. Generally, the speckle noises are scattered, in satellite images, medical images and synthetic aperture radar (SAR) images. This paper introduces a bidimensional empirical mode decomposition (BEMD)-based adaptive filtering method for despeckling of SAR image. The noisy SAR image is decomposed into different bidimensional intrinsic mode function (BIMF) levels using BEMD and then filtering is performed on the first BIMF level, as it contains the high-frequency noise component. This adaptation process effectively filters out the noisy image component without destroying the original image component. A BEMD-based adaptive Frost filter is introduced in this paper for despeckling of SAR images. The despeckling performances of our proposed filtering method are further analyzed by visual evaluation and also using performance parameters comparatively. Our reconstructed images show better performance quantitatively and qualitatively compared to other filters. Adaptive filters (dpeaa)DE-He213 BEMD (dpeaa)DE-He213 Synthetic aperture radar (dpeaa)DE-He213 Speckle noise (dpeaa)DE-He213 Image reconstruction (dpeaa)DE-He213 Suchetha, M. aut Enthalten in Journal of the Indian Society of Remote Sensing Neu Delhi : Springer India, 2008 51(2022), 9 vom: 24. Jan., Seite 1879-1890 (DE-627)573088853 (DE-600)2439566-3 0974-3006 nnns volume:51 year:2022 number:9 day:24 month:01 pages:1879-1890 https://dx.doi.org/10.1007/s12524-022-01495-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 51 2022 9 24 01 1879-1890 |
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Painam, Ranjith Kumar |
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Painam, Ranjith Kumar misc Adaptive filters misc BEMD misc Synthetic aperture radar misc Speckle noise misc Image reconstruction Despeckling of SAR Images Using BEMD-Based Adaptive Frost Filter |
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Despeckling of SAR Images Using BEMD-Based Adaptive Frost Filter Adaptive filters (dpeaa)DE-He213 BEMD (dpeaa)DE-He213 Synthetic aperture radar (dpeaa)DE-He213 Speckle noise (dpeaa)DE-He213 Image reconstruction (dpeaa)DE-He213 |
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Despeckling of SAR Images Using BEMD-Based Adaptive Frost Filter |
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Despeckling of SAR Images Using BEMD-Based Adaptive Frost Filter |
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despeckling of sar images using bemd-based adaptive frost filter |
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Despeckling of SAR Images Using BEMD-Based Adaptive Frost Filter |
abstract |
Abstract In image processing, removal of speckle noise from a satellite image is a challenging task for the researchers. There are various approaches for speckle noise reduction. Generally, the speckle noises are scattered, in satellite images, medical images and synthetic aperture radar (SAR) images. This paper introduces a bidimensional empirical mode decomposition (BEMD)-based adaptive filtering method for despeckling of SAR image. The noisy SAR image is decomposed into different bidimensional intrinsic mode function (BIMF) levels using BEMD and then filtering is performed on the first BIMF level, as it contains the high-frequency noise component. This adaptation process effectively filters out the noisy image component without destroying the original image component. A BEMD-based adaptive Frost filter is introduced in this paper for despeckling of SAR images. The despeckling performances of our proposed filtering method are further analyzed by visual evaluation and also using performance parameters comparatively. Our reconstructed images show better performance quantitatively and qualitatively compared to other filters. © Indian Society of Remote Sensing 2022 |
abstractGer |
Abstract In image processing, removal of speckle noise from a satellite image is a challenging task for the researchers. There are various approaches for speckle noise reduction. Generally, the speckle noises are scattered, in satellite images, medical images and synthetic aperture radar (SAR) images. This paper introduces a bidimensional empirical mode decomposition (BEMD)-based adaptive filtering method for despeckling of SAR image. The noisy SAR image is decomposed into different bidimensional intrinsic mode function (BIMF) levels using BEMD and then filtering is performed on the first BIMF level, as it contains the high-frequency noise component. This adaptation process effectively filters out the noisy image component without destroying the original image component. A BEMD-based adaptive Frost filter is introduced in this paper for despeckling of SAR images. The despeckling performances of our proposed filtering method are further analyzed by visual evaluation and also using performance parameters comparatively. Our reconstructed images show better performance quantitatively and qualitatively compared to other filters. © Indian Society of Remote Sensing 2022 |
abstract_unstemmed |
Abstract In image processing, removal of speckle noise from a satellite image is a challenging task for the researchers. There are various approaches for speckle noise reduction. Generally, the speckle noises are scattered, in satellite images, medical images and synthetic aperture radar (SAR) images. This paper introduces a bidimensional empirical mode decomposition (BEMD)-based adaptive filtering method for despeckling of SAR image. The noisy SAR image is decomposed into different bidimensional intrinsic mode function (BIMF) levels using BEMD and then filtering is performed on the first BIMF level, as it contains the high-frequency noise component. This adaptation process effectively filters out the noisy image component without destroying the original image component. A BEMD-based adaptive Frost filter is introduced in this paper for despeckling of SAR images. The despeckling performances of our proposed filtering method are further analyzed by visual evaluation and also using performance parameters comparatively. Our reconstructed images show better performance quantitatively and qualitatively compared to other filters. © Indian Society of Remote Sensing 2022 |
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Despeckling of SAR Images Using BEMD-Based Adaptive Frost Filter |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR05356572X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20231029064705.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">231029s2022 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s12524-022-01495-x</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR05356572X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s12524-022-01495-x-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Painam, Ranjith Kumar</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Despeckling of SAR Images Using BEMD-Based Adaptive Frost Filter</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Indian Society of Remote Sensing 2022</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract In image processing, removal of speckle noise from a satellite image is a challenging task for the researchers. There are various approaches for speckle noise reduction. Generally, the speckle noises are scattered, in satellite images, medical images and synthetic aperture radar (SAR) images. This paper introduces a bidimensional empirical mode decomposition (BEMD)-based adaptive filtering method for despeckling of SAR image. The noisy SAR image is decomposed into different bidimensional intrinsic mode function (BIMF) levels using BEMD and then filtering is performed on the first BIMF level, as it contains the high-frequency noise component. This adaptation process effectively filters out the noisy image component without destroying the original image component. A BEMD-based adaptive Frost filter is introduced in this paper for despeckling of SAR images. The despeckling performances of our proposed filtering method are further analyzed by visual evaluation and also using performance parameters comparatively. Our reconstructed images show better performance quantitatively and qualitatively compared to other filters.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Adaptive filters</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">BEMD</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Synthetic aperture radar</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Speckle noise</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Image reconstruction</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Suchetha, M.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of the Indian Society of Remote Sensing</subfield><subfield code="d">Neu Delhi : Springer India, 2008</subfield><subfield code="g">51(2022), 9 vom: 24. Jan., Seite 1879-1890</subfield><subfield code="w">(DE-627)573088853</subfield><subfield code="w">(DE-600)2439566-3</subfield><subfield code="x">0974-3006</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:51</subfield><subfield code="g">year:2022</subfield><subfield code="g">number:9</subfield><subfield code="g">day:24</subfield><subfield code="g">month:01</subfield><subfield code="g">pages:1879-1890</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s12524-022-01495-x</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield 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