Optimization of motion estimation hardware using charged system optimization with low power multipliers for H.264 encoders

Abstract Motion estimation has a critical role to play in the transmission and compression of digital video. As it has a complexity in terms of computation that is inherent it is a big challenge for the implementation of real time codes. Recently there have been studies on block matching algorithms...
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Gespeichert in:

Autor*in:	Vigneash, L. [verfasserIn] Marimuthu, C. N. [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2017

Schlagwörter:	Motion estimation Video compression Block matching algorithm (BMA) Charged system search (CSS) and Full search algorithm (FSA)

Übergeordnetes Werk:	Enthalten in: Cluster computing - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1998, 22(2017), Suppl 5 vom: 26. Sept., Seite 10669-10677
Übergeordnetes Werk:	volume:22 ; year:2017 ; number:Suppl 5 ; day:26 ; month:09 ; pages:10669-10677

Links:	Volltext

DOI / URN:	10.1007/s10586-017-1155-2

Katalog-ID:	SPR011521171

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245	1	0	\|a Optimization of motion estimation hardware using charged system optimization with low power multipliers for H.264 encoders
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520			\|a Abstract Motion estimation has a critical role to play in the transmission and compression of digital video. As it has a complexity in terms of computation that is inherent it is a big challenge for the implementation of real time codes. Recently there have been studies on block matching algorithms (BMA) for bringing down the complexity in the computation and has also got better attention in many algorithms that are very effective for very large scale integration (VLSI) systems for bringing down the complexity. These BMA algorithms are relatively easy to implement which can give solutions that are suboptimal even if the entire search has not been performed. The entire search is high in terms of cost of computation that prevents it from being applied in the systems of VLSI. A novel and fast motion estimation based algorithm known as charged system search (CSS) and full search algorithm (FSA) for multipliers of low power and for H.264 encoders is proposed. The CSS is used in all fields of optimization and is well suited for most domains and does not require any gradient information. The results have proved that proposed FSA has better performance.
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650		4	\|a Block matching algorithm (BMA) \|7 (dpeaa)DE-He213
650		4	\|a Charged system search (CSS) and Full search algorithm (FSA) \|7 (dpeaa)DE-He213
700	1		\|a Marimuthu, C. N. \|e verfasserin \|4 aut
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matchkey_str	article:15737543:2017----::piiainfoinsiainadaesncagdytmpiiainihopw
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publishDate	2017
allfields	10.1007/s10586-017-1155-2 doi (DE-627)SPR011521171 (SPR)s10586-017-1155-2-e DE-627 ger DE-627 rakwb eng 004 ASE 54.50 bkl 54.32 bkl 54.25 bkl Vigneash, L. verfasserin aut Optimization of motion estimation hardware using charged system optimization with low power multipliers for H.264 encoders 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Motion estimation has a critical role to play in the transmission and compression of digital video. As it has a complexity in terms of computation that is inherent it is a big challenge for the implementation of real time codes. Recently there have been studies on block matching algorithms (BMA) for bringing down the complexity in the computation and has also got better attention in many algorithms that are very effective for very large scale integration (VLSI) systems for bringing down the complexity. These BMA algorithms are relatively easy to implement which can give solutions that are suboptimal even if the entire search has not been performed. The entire search is high in terms of cost of computation that prevents it from being applied in the systems of VLSI. A novel and fast motion estimation based algorithm known as charged system search (CSS) and full search algorithm (FSA) for multipliers of low power and for H.264 encoders is proposed. The CSS is used in all fields of optimization and is well suited for most domains and does not require any gradient information. The results have proved that proposed FSA has better performance. Motion estimation (dpeaa)DE-He213 Video compression (dpeaa)DE-He213 Block matching algorithm (BMA) (dpeaa)DE-He213 Charged system search (CSS) and Full search algorithm (FSA) (dpeaa)DE-He213 Marimuthu, C. N. verfasserin aut Enthalten in Cluster computing Dordrecht [u.a.] : Springer Science + Business Media B.V, 1998 22(2017), Suppl 5 vom: 26. Sept., Seite 10669-10677 (DE-627)320505332 (DE-600)2012757-1 1573-7543 nnns volume:22 year:2017 number:Suppl 5 day:26 month:09 pages:10669-10677 https://dx.doi.org/10.1007/s10586-017-1155-2 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_101 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_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_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 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 54.50 ASE 54.32 ASE 54.25 ASE AR 22 2017 Suppl 5 26 09 10669-10677
spelling	10.1007/s10586-017-1155-2 doi (DE-627)SPR011521171 (SPR)s10586-017-1155-2-e DE-627 ger DE-627 rakwb eng 004 ASE 54.50 bkl 54.32 bkl 54.25 bkl Vigneash, L. verfasserin aut Optimization of motion estimation hardware using charged system optimization with low power multipliers for H.264 encoders 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Motion estimation has a critical role to play in the transmission and compression of digital video. As it has a complexity in terms of computation that is inherent it is a big challenge for the implementation of real time codes. Recently there have been studies on block matching algorithms (BMA) for bringing down the complexity in the computation and has also got better attention in many algorithms that are very effective for very large scale integration (VLSI) systems for bringing down the complexity. These BMA algorithms are relatively easy to implement which can give solutions that are suboptimal even if the entire search has not been performed. The entire search is high in terms of cost of computation that prevents it from being applied in the systems of VLSI. A novel and fast motion estimation based algorithm known as charged system search (CSS) and full search algorithm (FSA) for multipliers of low power and for H.264 encoders is proposed. The CSS is used in all fields of optimization and is well suited for most domains and does not require any gradient information. The results have proved that proposed FSA has better performance. Motion estimation (dpeaa)DE-He213 Video compression (dpeaa)DE-He213 Block matching algorithm (BMA) (dpeaa)DE-He213 Charged system search (CSS) and Full search algorithm (FSA) (dpeaa)DE-He213 Marimuthu, C. N. verfasserin aut Enthalten in Cluster computing Dordrecht [u.a.] : Springer Science + Business Media B.V, 1998 22(2017), Suppl 5 vom: 26. Sept., Seite 10669-10677 (DE-627)320505332 (DE-600)2012757-1 1573-7543 nnns volume:22 year:2017 number:Suppl 5 day:26 month:09 pages:10669-10677 https://dx.doi.org/10.1007/s10586-017-1155-2 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_101 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_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_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 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 54.50 ASE 54.32 ASE 54.25 ASE AR 22 2017 Suppl 5 26 09 10669-10677
allfields_unstemmed	10.1007/s10586-017-1155-2 doi (DE-627)SPR011521171 (SPR)s10586-017-1155-2-e DE-627 ger DE-627 rakwb eng 004 ASE 54.50 bkl 54.32 bkl 54.25 bkl Vigneash, L. verfasserin aut Optimization of motion estimation hardware using charged system optimization with low power multipliers for H.264 encoders 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Motion estimation has a critical role to play in the transmission and compression of digital video. As it has a complexity in terms of computation that is inherent it is a big challenge for the implementation of real time codes. Recently there have been studies on block matching algorithms (BMA) for bringing down the complexity in the computation and has also got better attention in many algorithms that are very effective for very large scale integration (VLSI) systems for bringing down the complexity. These BMA algorithms are relatively easy to implement which can give solutions that are suboptimal even if the entire search has not been performed. The entire search is high in terms of cost of computation that prevents it from being applied in the systems of VLSI. A novel and fast motion estimation based algorithm known as charged system search (CSS) and full search algorithm (FSA) for multipliers of low power and for H.264 encoders is proposed. The CSS is used in all fields of optimization and is well suited for most domains and does not require any gradient information. The results have proved that proposed FSA has better performance. Motion estimation (dpeaa)DE-He213 Video compression (dpeaa)DE-He213 Block matching algorithm (BMA) (dpeaa)DE-He213 Charged system search (CSS) and Full search algorithm (FSA) (dpeaa)DE-He213 Marimuthu, C. N. verfasserin aut Enthalten in Cluster computing Dordrecht [u.a.] : Springer Science + Business Media B.V, 1998 22(2017), Suppl 5 vom: 26. Sept., Seite 10669-10677 (DE-627)320505332 (DE-600)2012757-1 1573-7543 nnns volume:22 year:2017 number:Suppl 5 day:26 month:09 pages:10669-10677 https://dx.doi.org/10.1007/s10586-017-1155-2 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_101 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_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_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 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 54.50 ASE 54.32 ASE 54.25 ASE AR 22 2017 Suppl 5 26 09 10669-10677
allfieldsGer	10.1007/s10586-017-1155-2 doi (DE-627)SPR011521171 (SPR)s10586-017-1155-2-e DE-627 ger DE-627 rakwb eng 004 ASE 54.50 bkl 54.32 bkl 54.25 bkl Vigneash, L. verfasserin aut Optimization of motion estimation hardware using charged system optimization with low power multipliers for H.264 encoders 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Motion estimation has a critical role to play in the transmission and compression of digital video. As it has a complexity in terms of computation that is inherent it is a big challenge for the implementation of real time codes. Recently there have been studies on block matching algorithms (BMA) for bringing down the complexity in the computation and has also got better attention in many algorithms that are very effective for very large scale integration (VLSI) systems for bringing down the complexity. These BMA algorithms are relatively easy to implement which can give solutions that are suboptimal even if the entire search has not been performed. The entire search is high in terms of cost of computation that prevents it from being applied in the systems of VLSI. A novel and fast motion estimation based algorithm known as charged system search (CSS) and full search algorithm (FSA) for multipliers of low power and for H.264 encoders is proposed. The CSS is used in all fields of optimization and is well suited for most domains and does not require any gradient information. The results have proved that proposed FSA has better performance. Motion estimation (dpeaa)DE-He213 Video compression (dpeaa)DE-He213 Block matching algorithm (BMA) (dpeaa)DE-He213 Charged system search (CSS) and Full search algorithm (FSA) (dpeaa)DE-He213 Marimuthu, C. N. verfasserin aut Enthalten in Cluster computing Dordrecht [u.a.] : Springer Science + Business Media B.V, 1998 22(2017), Suppl 5 vom: 26. Sept., Seite 10669-10677 (DE-627)320505332 (DE-600)2012757-1 1573-7543 nnns volume:22 year:2017 number:Suppl 5 day:26 month:09 pages:10669-10677 https://dx.doi.org/10.1007/s10586-017-1155-2 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_101 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_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_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 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 54.50 ASE 54.32 ASE 54.25 ASE AR 22 2017 Suppl 5 26 09 10669-10677
allfieldsSound	10.1007/s10586-017-1155-2 doi (DE-627)SPR011521171 (SPR)s10586-017-1155-2-e DE-627 ger DE-627 rakwb eng 004 ASE 54.50 bkl 54.32 bkl 54.25 bkl Vigneash, L. verfasserin aut Optimization of motion estimation hardware using charged system optimization with low power multipliers for H.264 encoders 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Motion estimation has a critical role to play in the transmission and compression of digital video. As it has a complexity in terms of computation that is inherent it is a big challenge for the implementation of real time codes. Recently there have been studies on block matching algorithms (BMA) for bringing down the complexity in the computation and has also got better attention in many algorithms that are very effective for very large scale integration (VLSI) systems for bringing down the complexity. These BMA algorithms are relatively easy to implement which can give solutions that are suboptimal even if the entire search has not been performed. The entire search is high in terms of cost of computation that prevents it from being applied in the systems of VLSI. A novel and fast motion estimation based algorithm known as charged system search (CSS) and full search algorithm (FSA) for multipliers of low power and for H.264 encoders is proposed. The CSS is used in all fields of optimization and is well suited for most domains and does not require any gradient information. The results have proved that proposed FSA has better performance. Motion estimation (dpeaa)DE-He213 Video compression (dpeaa)DE-He213 Block matching algorithm (BMA) (dpeaa)DE-He213 Charged system search (CSS) and Full search algorithm (FSA) (dpeaa)DE-He213 Marimuthu, C. N. verfasserin aut Enthalten in Cluster computing Dordrecht [u.a.] : Springer Science + Business Media B.V, 1998 22(2017), Suppl 5 vom: 26. Sept., Seite 10669-10677 (DE-627)320505332 (DE-600)2012757-1 1573-7543 nnns volume:22 year:2017 number:Suppl 5 day:26 month:09 pages:10669-10677 https://dx.doi.org/10.1007/s10586-017-1155-2 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_101 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_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_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 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 54.50 ASE 54.32 ASE 54.25 ASE AR 22 2017 Suppl 5 26 09 10669-10677
language	English
source	Enthalten in Cluster computing 22(2017), Suppl 5 vom: 26. Sept., Seite 10669-10677 volume:22 year:2017 number:Suppl 5 day:26 month:09 pages:10669-10677
sourceStr	Enthalten in Cluster computing 22(2017), Suppl 5 vom: 26. Sept., Seite 10669-10677 volume:22 year:2017 number:Suppl 5 day:26 month:09 pages:10669-10677
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Motion estimation Video compression Block matching algorithm (BMA) Charged system search (CSS) and Full search algorithm (FSA)
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container_title	Cluster computing
authorswithroles_txt_mv	Vigneash, L. @@aut@@ Marimuthu, C. N. @@aut@@
publishDateDaySort_date	2017-09-26T00:00:00Z
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author	Vigneash, L.
spellingShingle	Vigneash, L. ddc 004 bkl 54.50 bkl 54.32 bkl 54.25 misc Motion estimation misc Video compression misc Block matching algorithm (BMA) misc Charged system search (CSS) and Full search algorithm (FSA) Optimization of motion estimation hardware using charged system optimization with low power multipliers for H.264 encoders
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topic_title	004 ASE 54.50 bkl 54.32 bkl 54.25 bkl Optimization of motion estimation hardware using charged system optimization with low power multipliers for H.264 encoders Motion estimation (dpeaa)DE-He213 Video compression (dpeaa)DE-He213 Block matching algorithm (BMA) (dpeaa)DE-He213 Charged system search (CSS) and Full search algorithm (FSA) (dpeaa)DE-He213
topic	ddc 004 bkl 54.50 bkl 54.32 bkl 54.25 misc Motion estimation misc Video compression misc Block matching algorithm (BMA) misc Charged system search (CSS) and Full search algorithm (FSA)
topic_unstemmed	ddc 004 bkl 54.50 bkl 54.32 bkl 54.25 misc Motion estimation misc Video compression misc Block matching algorithm (BMA) misc Charged system search (CSS) and Full search algorithm (FSA)
topic_browse	ddc 004 bkl 54.50 bkl 54.32 bkl 54.25 misc Motion estimation misc Video compression misc Block matching algorithm (BMA) misc Charged system search (CSS) and Full search algorithm (FSA)
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title_full	Optimization of motion estimation hardware using charged system optimization with low power multipliers for H.264 encoders
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title_sort	optimization of motion estimation hardware using charged system optimization with low power multipliers for h.264 encoders
title_auth	Optimization of motion estimation hardware using charged system optimization with low power multipliers for H.264 encoders
abstract	Abstract Motion estimation has a critical role to play in the transmission and compression of digital video. As it has a complexity in terms of computation that is inherent it is a big challenge for the implementation of real time codes. Recently there have been studies on block matching algorithms (BMA) for bringing down the complexity in the computation and has also got better attention in many algorithms that are very effective for very large scale integration (VLSI) systems for bringing down the complexity. These BMA algorithms are relatively easy to implement which can give solutions that are suboptimal even if the entire search has not been performed. The entire search is high in terms of cost of computation that prevents it from being applied in the systems of VLSI. A novel and fast motion estimation based algorithm known as charged system search (CSS) and full search algorithm (FSA) for multipliers of low power and for H.264 encoders is proposed. The CSS is used in all fields of optimization and is well suited for most domains and does not require any gradient information. The results have proved that proposed FSA has better performance.
abstractGer	Abstract Motion estimation has a critical role to play in the transmission and compression of digital video. As it has a complexity in terms of computation that is inherent it is a big challenge for the implementation of real time codes. Recently there have been studies on block matching algorithms (BMA) for bringing down the complexity in the computation and has also got better attention in many algorithms that are very effective for very large scale integration (VLSI) systems for bringing down the complexity. These BMA algorithms are relatively easy to implement which can give solutions that are suboptimal even if the entire search has not been performed. The entire search is high in terms of cost of computation that prevents it from being applied in the systems of VLSI. A novel and fast motion estimation based algorithm known as charged system search (CSS) and full search algorithm (FSA) for multipliers of low power and for H.264 encoders is proposed. The CSS is used in all fields of optimization and is well suited for most domains and does not require any gradient information. The results have proved that proposed FSA has better performance.
abstract_unstemmed	Abstract Motion estimation has a critical role to play in the transmission and compression of digital video. As it has a complexity in terms of computation that is inherent it is a big challenge for the implementation of real time codes. Recently there have been studies on block matching algorithms (BMA) for bringing down the complexity in the computation and has also got better attention in many algorithms that are very effective for very large scale integration (VLSI) systems for bringing down the complexity. These BMA algorithms are relatively easy to implement which can give solutions that are suboptimal even if the entire search has not been performed. The entire search is high in terms of cost of computation that prevents it from being applied in the systems of VLSI. A novel and fast motion estimation based algorithm known as charged system search (CSS) and full search algorithm (FSA) for multipliers of low power and for H.264 encoders is proposed. The CSS is used in all fields of optimization and is well suited for most domains and does not require any gradient information. The results have proved that proposed FSA has better performance.
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container_issue	Suppl 5
title_short	Optimization of motion estimation hardware using charged system optimization with low power multipliers for H.264 encoders
url	https://dx.doi.org/10.1007/s10586-017-1155-2
remote_bool	true
author2	Marimuthu, C. N.
author2Str	Marimuthu, C. N.
ppnlink	320505332
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doi_str	10.1007/s10586-017-1155-2
up_date	2024-07-03T23:09:08.956Z
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Optimization of motion estimation hardware using charged system optimization with low power multipliers for H.264 encoders

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