Tikhonov-regularized bispectral variational method for optical signal reconstruction
A Tikhonov-regularized bispectral variational method is proposed for image restoration in the presence of strong phase distortions. This method combines a number of advantages of the bispectral approach, such as preservation and restoration of phase information, invariance to random shifts of the or...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Iroshnikov, N. G. [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2013 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media New York 2013 |
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| Übergeordnetes Werk: |
Enthalten in: Computational mathematics and modeling - Springer US, 1990, 24(2013), 4 vom: 31. Aug., Seite 505-516 |
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| Übergeordnetes Werk: |
volume:24 ; year:2013 ; number:4 ; day:31 ; month:08 ; pages:505-516 |
| Links: |
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| DOI / URN: |
10.1007/s10598-013-9194-x |
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OLC2044592053 |
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| 520 | |a A Tikhonov-regularized bispectral variational method is proposed for image restoration in the presence of strong phase distortions. This method combines a number of advantages of the bispectral approach, such as preservation and restoration of phase information, invariance to random shifts of the original signal, and no requirement of high-accuracy prior information about statistical properties of observed signals. In combination with the Tikhonov-regularized variational method, which is adapted to stable processing of large images, we obtain a fairly efficient image restoration method. Test results in the presence of atmospheric and underwater phase distortions reported in this article establish the advantages of the proposed method relative to the traditional recursive bispectral method. | ||
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10.1007/s10598-013-9194-x doi (DE-627)OLC2044592053 (DE-He213)s10598-013-9194-x-p DE-627 ger DE-627 rakwb eng 004 VZ Iroshnikov, N. G. verfasserin aut Tikhonov-regularized bispectral variational method for optical signal reconstruction 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2013 A Tikhonov-regularized bispectral variational method is proposed for image restoration in the presence of strong phase distortions. This method combines a number of advantages of the bispectral approach, such as preservation and restoration of phase information, invariance to random shifts of the original signal, and no requirement of high-accuracy prior information about statistical properties of observed signals. In combination with the Tikhonov-regularized variational method, which is adapted to stable processing of large images, we obtain a fairly efficient image restoration method. Test results in the presence of atmospheric and underwater phase distortions reported in this article establish the advantages of the proposed method relative to the traditional recursive bispectral method. bispectrum triple correlation reconstruction of phase distortions variational method Tikhonov regularization regularized gradient method Larichev, A. V. aut Potyagalova, A. A. aut Razgulin, A. V. aut Enthalten in Computational mathematics and modeling Springer US, 1990 24(2013), 4 vom: 31. Aug., Seite 505-516 (DE-627)130898163 (DE-600)1043251-6 (DE-576)034187774 1046-283X nnns volume:24 year:2013 number:4 day:31 month:08 pages:505-516 https://doi.org/10.1007/s10598-013-9194-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_2012 AR 24 2013 4 31 08 505-516 |
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10.1007/s10598-013-9194-x doi (DE-627)OLC2044592053 (DE-He213)s10598-013-9194-x-p DE-627 ger DE-627 rakwb eng 004 VZ Iroshnikov, N. G. verfasserin aut Tikhonov-regularized bispectral variational method for optical signal reconstruction 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2013 A Tikhonov-regularized bispectral variational method is proposed for image restoration in the presence of strong phase distortions. This method combines a number of advantages of the bispectral approach, such as preservation and restoration of phase information, invariance to random shifts of the original signal, and no requirement of high-accuracy prior information about statistical properties of observed signals. In combination with the Tikhonov-regularized variational method, which is adapted to stable processing of large images, we obtain a fairly efficient image restoration method. Test results in the presence of atmospheric and underwater phase distortions reported in this article establish the advantages of the proposed method relative to the traditional recursive bispectral method. bispectrum triple correlation reconstruction of phase distortions variational method Tikhonov regularization regularized gradient method Larichev, A. V. aut Potyagalova, A. A. aut Razgulin, A. V. aut Enthalten in Computational mathematics and modeling Springer US, 1990 24(2013), 4 vom: 31. Aug., Seite 505-516 (DE-627)130898163 (DE-600)1043251-6 (DE-576)034187774 1046-283X nnns volume:24 year:2013 number:4 day:31 month:08 pages:505-516 https://doi.org/10.1007/s10598-013-9194-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_2012 AR 24 2013 4 31 08 505-516 |
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10.1007/s10598-013-9194-x doi (DE-627)OLC2044592053 (DE-He213)s10598-013-9194-x-p DE-627 ger DE-627 rakwb eng 004 VZ Iroshnikov, N. G. verfasserin aut Tikhonov-regularized bispectral variational method for optical signal reconstruction 2013 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2013 A Tikhonov-regularized bispectral variational method is proposed for image restoration in the presence of strong phase distortions. This method combines a number of advantages of the bispectral approach, such as preservation and restoration of phase information, invariance to random shifts of the original signal, and no requirement of high-accuracy prior information about statistical properties of observed signals. In combination with the Tikhonov-regularized variational method, which is adapted to stable processing of large images, we obtain a fairly efficient image restoration method. Test results in the presence of atmospheric and underwater phase distortions reported in this article establish the advantages of the proposed method relative to the traditional recursive bispectral method. bispectrum triple correlation reconstruction of phase distortions variational method Tikhonov regularization regularized gradient method Larichev, A. V. aut Potyagalova, A. A. aut Razgulin, A. V. aut Enthalten in Computational mathematics and modeling Springer US, 1990 24(2013), 4 vom: 31. Aug., Seite 505-516 (DE-627)130898163 (DE-600)1043251-6 (DE-576)034187774 1046-283X nnns volume:24 year:2013 number:4 day:31 month:08 pages:505-516 https://doi.org/10.1007/s10598-013-9194-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_2012 AR 24 2013 4 31 08 505-516 |
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A Tikhonov-regularized bispectral variational method is proposed for image restoration in the presence of strong phase distortions. This method combines a number of advantages of the bispectral approach, such as preservation and restoration of phase information, invariance to random shifts of the original signal, and no requirement of high-accuracy prior information about statistical properties of observed signals. In combination with the Tikhonov-regularized variational method, which is adapted to stable processing of large images, we obtain a fairly efficient image restoration method. Test results in the presence of atmospheric and underwater phase distortions reported in this article establish the advantages of the proposed method relative to the traditional recursive bispectral method. © Springer Science+Business Media New York 2013 |
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A Tikhonov-regularized bispectral variational method is proposed for image restoration in the presence of strong phase distortions. This method combines a number of advantages of the bispectral approach, such as preservation and restoration of phase information, invariance to random shifts of the original signal, and no requirement of high-accuracy prior information about statistical properties of observed signals. In combination with the Tikhonov-regularized variational method, which is adapted to stable processing of large images, we obtain a fairly efficient image restoration method. Test results in the presence of atmospheric and underwater phase distortions reported in this article establish the advantages of the proposed method relative to the traditional recursive bispectral method. © Springer Science+Business Media New York 2013 |
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A Tikhonov-regularized bispectral variational method is proposed for image restoration in the presence of strong phase distortions. This method combines a number of advantages of the bispectral approach, such as preservation and restoration of phase information, invariance to random shifts of the original signal, and no requirement of high-accuracy prior information about statistical properties of observed signals. In combination with the Tikhonov-regularized variational method, which is adapted to stable processing of large images, we obtain a fairly efficient image restoration method. Test results in the presence of atmospheric and underwater phase distortions reported in this article establish the advantages of the proposed method relative to the traditional recursive bispectral method. © Springer Science+Business Media New York 2013 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2044592053</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230503031625.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200819s2013 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10598-013-9194-x</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2044592053</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s10598-013-9194-x-p</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="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Iroshnikov, N. G.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Tikhonov-regularized bispectral variational method for optical signal reconstruction</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2013</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">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media New York 2013</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">A Tikhonov-regularized bispectral variational method is proposed for image restoration in the presence of strong phase distortions. This method combines a number of advantages of the bispectral approach, such as preservation and restoration of phase information, invariance to random shifts of the original signal, and no requirement of high-accuracy prior information about statistical properties of observed signals. In combination with the Tikhonov-regularized variational method, which is adapted to stable processing of large images, we obtain a fairly efficient image restoration method. 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