Neighboring Coefficients Preservation for Signal Denoising

Abstract For traditional thresholding denoising, the wavelet coefficients are thresholded without considering the information of other coefficients. In this paper, we propose a novel denoising approach which incorporates the neighboring coefficients into signal denoising. Our approach not only prese...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Yang, Ying [verfasserIn] Wei, Yusen

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2011

Schlagwörter:	Wavelet transforms Shrinkage function Neighboring coefficients Signal denoising

Anmerkung:	© Springer Science+Business Media, LLC 2011

Übergeordnetes Werk:	Enthalten in: Circuits, systems and signal processing - Boston, Mass. : Birkhäuser, 1982, 31(2011), 2 vom: 27. Aug., Seite 827-832
Übergeordnetes Werk:	volume:31 ; year:2011 ; number:2 ; day:27 ; month:08 ; pages:827-832

Links:	Volltext

DOI / URN:	10.1007/s00034-011-9346-1

Katalog-ID:	SPR000493333

Internformat


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520			\|a Abstract For traditional thresholding denoising, the wavelet coefficients are thresholded without considering the information of other coefficients. In this paper, we propose a novel denoising approach which incorporates the neighboring coefficients into signal denoising. Our approach not only preserves the coefficients above the threshold, but it also preserves the coefficients predominated by useful components although their magnitudes are smaller than or equal to the threshold. Experimental results illustrate that the proposed approach is better than the NeighShrink scheme and the hard thresholding in both of the visual perception and the numerical results.
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650		4	\|a Neighboring coefficients \|7 (dpeaa)DE-He213
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912			\|a GBV_ILN_138
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912			\|a GBV_ILN_152
912			\|a GBV_ILN_161
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912			\|a GBV_ILN_187
912			\|a GBV_ILN_213
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912			\|a GBV_ILN_281
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_636
912			\|a GBV_ILN_702
912			\|a GBV_ILN_2001
912			\|a GBV_ILN_2003
912			\|a GBV_ILN_2004
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912			\|a GBV_ILN_2006
912			\|a GBV_ILN_2007
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912			\|a GBV_ILN_2010
912			\|a GBV_ILN_2011
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912			\|a GBV_ILN_2021
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912			\|a GBV_ILN_2026
912			\|a GBV_ILN_2027
912			\|a GBV_ILN_2031
912			\|a GBV_ILN_2034
912			\|a GBV_ILN_2037
912			\|a GBV_ILN_2038
912			\|a GBV_ILN_2039
912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2049
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2057
912			\|a GBV_ILN_2059
912			\|a GBV_ILN_2061
912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2065
912			\|a GBV_ILN_2068
912			\|a GBV_ILN_2070
912			\|a GBV_ILN_2086
912			\|a GBV_ILN_2088
912			\|a GBV_ILN_2093
912			\|a GBV_ILN_2106
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912			\|a GBV_ILN_2190
912			\|a GBV_ILN_2232
912			\|a GBV_ILN_2336
912			\|a GBV_ILN_2446
912			\|a GBV_ILN_2470
912			\|a GBV_ILN_2472
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912			\|a GBV_ILN_2522
912			\|a GBV_ILN_2548
912			\|a GBV_ILN_4012
912			\|a GBV_ILN_4035
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4046
912			\|a GBV_ILN_4112
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publishDate	2011
allfields	10.1007/s00034-011-9346-1 doi (DE-627)SPR000493333 (SPR)s00034-011-9346-1-e DE-627 ger DE-627 rakwb eng Yang, Ying verfasserin aut Neighboring Coefficients Preservation for Signal Denoising 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC 2011 Abstract For traditional thresholding denoising, the wavelet coefficients are thresholded without considering the information of other coefficients. In this paper, we propose a novel denoising approach which incorporates the neighboring coefficients into signal denoising. Our approach not only preserves the coefficients above the threshold, but it also preserves the coefficients predominated by useful components although their magnitudes are smaller than or equal to the threshold. Experimental results illustrate that the proposed approach is better than the NeighShrink scheme and the hard thresholding in both of the visual perception and the numerical results. Wavelet transforms (dpeaa)DE-He213 Shrinkage function (dpeaa)DE-He213 Neighboring coefficients (dpeaa)DE-He213 Signal denoising (dpeaa)DE-He213 Wei, Yusen aut Enthalten in Circuits, systems and signal processing Boston, Mass. : Birkhäuser, 1982 31(2011), 2 vom: 27. Aug., Seite 827-832 (DE-627)351975470 (DE-600)2085136-4 1531-5878 nnns volume:31 year:2011 number:2 day:27 month:08 pages:827-832 https://dx.doi.org/10.1007/s00034-011-9346-1 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_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_267 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_4012 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 31 2011 2 27 08 827-832
spelling	10.1007/s00034-011-9346-1 doi (DE-627)SPR000493333 (SPR)s00034-011-9346-1-e DE-627 ger DE-627 rakwb eng Yang, Ying verfasserin aut Neighboring Coefficients Preservation for Signal Denoising 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC 2011 Abstract For traditional thresholding denoising, the wavelet coefficients are thresholded without considering the information of other coefficients. In this paper, we propose a novel denoising approach which incorporates the neighboring coefficients into signal denoising. Our approach not only preserves the coefficients above the threshold, but it also preserves the coefficients predominated by useful components although their magnitudes are smaller than or equal to the threshold. Experimental results illustrate that the proposed approach is better than the NeighShrink scheme and the hard thresholding in both of the visual perception and the numerical results. Wavelet transforms (dpeaa)DE-He213 Shrinkage function (dpeaa)DE-He213 Neighboring coefficients (dpeaa)DE-He213 Signal denoising (dpeaa)DE-He213 Wei, Yusen aut Enthalten in Circuits, systems and signal processing Boston, Mass. : Birkhäuser, 1982 31(2011), 2 vom: 27. Aug., Seite 827-832 (DE-627)351975470 (DE-600)2085136-4 1531-5878 nnns volume:31 year:2011 number:2 day:27 month:08 pages:827-832 https://dx.doi.org/10.1007/s00034-011-9346-1 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_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_267 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_4012 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 31 2011 2 27 08 827-832
allfields_unstemmed	10.1007/s00034-011-9346-1 doi (DE-627)SPR000493333 (SPR)s00034-011-9346-1-e DE-627 ger DE-627 rakwb eng Yang, Ying verfasserin aut Neighboring Coefficients Preservation for Signal Denoising 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC 2011 Abstract For traditional thresholding denoising, the wavelet coefficients are thresholded without considering the information of other coefficients. In this paper, we propose a novel denoising approach which incorporates the neighboring coefficients into signal denoising. Our approach not only preserves the coefficients above the threshold, but it also preserves the coefficients predominated by useful components although their magnitudes are smaller than or equal to the threshold. Experimental results illustrate that the proposed approach is better than the NeighShrink scheme and the hard thresholding in both of the visual perception and the numerical results. Wavelet transforms (dpeaa)DE-He213 Shrinkage function (dpeaa)DE-He213 Neighboring coefficients (dpeaa)DE-He213 Signal denoising (dpeaa)DE-He213 Wei, Yusen aut Enthalten in Circuits, systems and signal processing Boston, Mass. : Birkhäuser, 1982 31(2011), 2 vom: 27. Aug., Seite 827-832 (DE-627)351975470 (DE-600)2085136-4 1531-5878 nnns volume:31 year:2011 number:2 day:27 month:08 pages:827-832 https://dx.doi.org/10.1007/s00034-011-9346-1 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_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_267 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_4012 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 31 2011 2 27 08 827-832
allfieldsGer	10.1007/s00034-011-9346-1 doi (DE-627)SPR000493333 (SPR)s00034-011-9346-1-e DE-627 ger DE-627 rakwb eng Yang, Ying verfasserin aut Neighboring Coefficients Preservation for Signal Denoising 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC 2011 Abstract For traditional thresholding denoising, the wavelet coefficients are thresholded without considering the information of other coefficients. In this paper, we propose a novel denoising approach which incorporates the neighboring coefficients into signal denoising. Our approach not only preserves the coefficients above the threshold, but it also preserves the coefficients predominated by useful components although their magnitudes are smaller than or equal to the threshold. Experimental results illustrate that the proposed approach is better than the NeighShrink scheme and the hard thresholding in both of the visual perception and the numerical results. Wavelet transforms (dpeaa)DE-He213 Shrinkage function (dpeaa)DE-He213 Neighboring coefficients (dpeaa)DE-He213 Signal denoising (dpeaa)DE-He213 Wei, Yusen aut Enthalten in Circuits, systems and signal processing Boston, Mass. : Birkhäuser, 1982 31(2011), 2 vom: 27. Aug., Seite 827-832 (DE-627)351975470 (DE-600)2085136-4 1531-5878 nnns volume:31 year:2011 number:2 day:27 month:08 pages:827-832 https://dx.doi.org/10.1007/s00034-011-9346-1 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_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_267 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_4012 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 31 2011 2 27 08 827-832
allfieldsSound	10.1007/s00034-011-9346-1 doi (DE-627)SPR000493333 (SPR)s00034-011-9346-1-e DE-627 ger DE-627 rakwb eng Yang, Ying verfasserin aut Neighboring Coefficients Preservation for Signal Denoising 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, LLC 2011 Abstract For traditional thresholding denoising, the wavelet coefficients are thresholded without considering the information of other coefficients. In this paper, we propose a novel denoising approach which incorporates the neighboring coefficients into signal denoising. Our approach not only preserves the coefficients above the threshold, but it also preserves the coefficients predominated by useful components although their magnitudes are smaller than or equal to the threshold. Experimental results illustrate that the proposed approach is better than the NeighShrink scheme and the hard thresholding in both of the visual perception and the numerical results. Wavelet transforms (dpeaa)DE-He213 Shrinkage function (dpeaa)DE-He213 Neighboring coefficients (dpeaa)DE-He213 Signal denoising (dpeaa)DE-He213 Wei, Yusen aut Enthalten in Circuits, systems and signal processing Boston, Mass. : Birkhäuser, 1982 31(2011), 2 vom: 27. Aug., Seite 827-832 (DE-627)351975470 (DE-600)2085136-4 1531-5878 nnns volume:31 year:2011 number:2 day:27 month:08 pages:827-832 https://dx.doi.org/10.1007/s00034-011-9346-1 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_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_267 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_4012 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 31 2011 2 27 08 827-832
language	English
source	Enthalten in Circuits, systems and signal processing 31(2011), 2 vom: 27. Aug., Seite 827-832 volume:31 year:2011 number:2 day:27 month:08 pages:827-832
sourceStr	Enthalten in Circuits, systems and signal processing 31(2011), 2 vom: 27. Aug., Seite 827-832 volume:31 year:2011 number:2 day:27 month:08 pages:827-832
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Wavelet transforms Shrinkage function Neighboring coefficients Signal denoising
isfreeaccess_bool	false
container_title	Circuits, systems and signal processing
authorswithroles_txt_mv	Yang, Ying @@aut@@ Wei, Yusen @@aut@@
publishDateDaySort_date	2011-08-27T00:00:00Z
hierarchy_top_id	351975470
id	SPR000493333
language_de	englisch
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author	Yang, Ying
spellingShingle	Yang, Ying misc Wavelet transforms misc Shrinkage function misc Neighboring coefficients misc Signal denoising Neighboring Coefficients Preservation for Signal Denoising
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topic_title	Neighboring Coefficients Preservation for Signal Denoising Wavelet transforms (dpeaa)DE-He213 Shrinkage function (dpeaa)DE-He213 Neighboring coefficients (dpeaa)DE-He213 Signal denoising (dpeaa)DE-He213
topic	misc Wavelet transforms misc Shrinkage function misc Neighboring coefficients misc Signal denoising
topic_unstemmed	misc Wavelet transforms misc Shrinkage function misc Neighboring coefficients misc Signal denoising
topic_browse	misc Wavelet transforms misc Shrinkage function misc Neighboring coefficients misc Signal denoising
format_facet	Elektronische Aufsätze Aufsätze Elektronische Ressource
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title	Neighboring Coefficients Preservation for Signal Denoising
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title_full	Neighboring Coefficients Preservation for Signal Denoising
author_sort	Yang, Ying
journal	Circuits, systems and signal processing
journalStr	Circuits, systems and signal processing
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author_browse	Yang, Ying Wei, Yusen
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format_se	Elektronische Aufsätze
author-letter	Yang, Ying
doi_str_mv	10.1007/s00034-011-9346-1
title_sort	neighboring coefficients preservation for signal denoising
title_auth	Neighboring Coefficients Preservation for Signal Denoising
abstract	Abstract For traditional thresholding denoising, the wavelet coefficients are thresholded without considering the information of other coefficients. In this paper, we propose a novel denoising approach which incorporates the neighboring coefficients into signal denoising. Our approach not only preserves the coefficients above the threshold, but it also preserves the coefficients predominated by useful components although their magnitudes are smaller than or equal to the threshold. Experimental results illustrate that the proposed approach is better than the NeighShrink scheme and the hard thresholding in both of the visual perception and the numerical results. © Springer Science+Business Media, LLC 2011
abstractGer	Abstract For traditional thresholding denoising, the wavelet coefficients are thresholded without considering the information of other coefficients. In this paper, we propose a novel denoising approach which incorporates the neighboring coefficients into signal denoising. Our approach not only preserves the coefficients above the threshold, but it also preserves the coefficients predominated by useful components although their magnitudes are smaller than or equal to the threshold. Experimental results illustrate that the proposed approach is better than the NeighShrink scheme and the hard thresholding in both of the visual perception and the numerical results. © Springer Science+Business Media, LLC 2011
abstract_unstemmed	Abstract For traditional thresholding denoising, the wavelet coefficients are thresholded without considering the information of other coefficients. In this paper, we propose a novel denoising approach which incorporates the neighboring coefficients into signal denoising. Our approach not only preserves the coefficients above the threshold, but it also preserves the coefficients predominated by useful components although their magnitudes are smaller than or equal to the threshold. Experimental results illustrate that the proposed approach is better than the NeighShrink scheme and the hard thresholding in both of the visual perception and the numerical results. © Springer Science+Business Media, LLC 2011
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title_short	Neighboring Coefficients Preservation for Signal Denoising
url	https://dx.doi.org/10.1007/s00034-011-9346-1
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doi_str	10.1007/s00034-011-9346-1
up_date	2024-07-03T16:26:40.658Z
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In this paper, we propose a novel denoising approach which incorporates the neighboring coefficients into signal denoising. Our approach not only preserves the coefficients above the threshold, but it also preserves the coefficients predominated by useful components although their magnitudes are smaller than or equal to the threshold. Experimental results illustrate that the proposed approach is better than the NeighShrink scheme and the hard thresholding in both of the visual perception and the numerical results.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Wavelet transforms</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Shrinkage function</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Neighboring coefficients</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Signal denoising</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wei, Yusen</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Circuits, systems and signal processing</subfield><subfield code="d">Boston, Mass. : Birkhäuser, 1982</subfield><subfield code="g">31(2011), 2 vom: 27. 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