Lossy compression of distributed sparse sources: A practical scheme

A new lossy compression scheme for distributed and sparse sources under a low complexity encoding constraint is proposed. This architecture is able to exploit both intra- and inter-signal correlations typical of signals monitored, for example, by a wireless sensor network. In order to meet the low c...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:2011 19th European Signal Processing Conference s. 422 - 426
Hlavní autori: Coluccia, G., Magli, E., Roumy, A., Toto-Zarasoa, V.
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 01.08.2011
Predmet:
Correlation
Decoding
Distortion measurement
Encoding
Joints
Quantization (signal)
Silicon
ISSN:2076-1465
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Abstract A new lossy compression scheme for distributed and sparse sources under a low complexity encoding constraint is proposed. This architecture is able to exploit both intra- and inter-signal correlations typical of signals monitored, for example, by a wireless sensor network. In order to meet the low complexity constraint, the encoding stage is performed by a lossy distributed compressed sensing (CS) algorithm. The novelty of the scheme consists in the combination of lossy distributed source coding (DSC) and CS. More precisely, we propose a joint CS reconstruction filter, which exploits the knowledge of the side information to improve the quality of both the dequantization and the CS reconstruction steps. The joint use of CS and DSC allows to achieve large bit-rate savings for the same quality with respect to the non-distributed CS scheme, e.g. up to 1.2 bps in the cases considered in this paper. Compared to the DSC scheme (without CS), we observe a gain increasing with the rate for the same mean square error.
AbstractList A new lossy compression scheme for distributed and sparse sources under a low complexity encoding constraint is proposed. This architecture is able to exploit both intra- and inter-signal correlations typical of signals monitored, for example, by a wireless sensor network. In order to meet the low complexity constraint, the encoding stage is performed by a lossy distributed compressed sensing (CS) algorithm. The novelty of the scheme consists in the combination of lossy distributed source coding (DSC) and CS. More precisely, we propose a joint CS reconstruction filter, which exploits the knowledge of the side information to improve the quality of both the dequantization and the CS reconstruction steps. The joint use of CS and DSC allows to achieve large bit-rate savings for the same quality with respect to the non-distributed CS scheme, e.g. up to 1.2 bps in the cases considered in this paper. Compared to the DSC scheme (without CS), we observe a gain increasing with the rate for the same mean square error.
Author Roumy, A.
Toto-Zarasoa, V.
Magli, E.
Coluccia, G.
Author_xml – sequence: 1
  givenname: G.
  surname: Coluccia
  fullname: Coluccia, G.
  organization: Politec. di Torino, Turin, Italy
– sequence: 2
  givenname: E.
  surname: Magli
  fullname: Magli, E.
  organization: Politec. di Torino, Turin, Italy
– sequence: 3
  givenname: A.
  surname: Roumy
  fullname: Roumy, A.
  organization: INRIA, Rennes, France
– sequence: 4
  givenname: V.
  surname: Toto-Zarasoa
  fullname: Toto-Zarasoa, V.
  organization: INRIA, Rennes, France
BookMark eNotzLtqwzAUgGENKTRN8wRZ9AIG3SzJ3YLpDQxZ2jnIR0dEEFtGxxny9i200z988D-xzVxm3LCtEs420tj2ke2J8iiUF95JYbesHwrRnUOZloq_VmZeEo-Z1prH24qR0xIqIadyq4D0wo98qQHWDOHKCS444TN7SOFKuP_vjn2_vX71H81wev_sj0OTpWjXpgWZUMmIIJIFobTvvJYSvRulCl3qWgNRJGNUMMF3Eq2LRqMCVNEkBL1jh79vRsTzUvMU6v3shDOytfoHlc9FuQ
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Xplore POP ALL
IEEE Xplore All Conference Proceedings
IEEE/IET Electronic Library
IEEE Proceedings Order Plans (POP All) 1998-Present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE/IET Electronic Library
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
EndPage 426
ExternalDocumentID 7074156
Genre orig-research
GroupedDBID 6IE
6IL
ACGFS
ALMA_UNASSIGNED_HOLDINGS
CBEJK
RIE
RIL
ID FETCH-LOGICAL-i105t-5c1fe21dec0f6c023898311e87b12a9f954cd0f442a4a891e67d43e2ce2d4fec3
IEDL.DBID RIE
ISICitedReferencesCount 12
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000377963100086&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 2076-1465
IngestDate Wed Aug 27 03:33:19 EDT 2025
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i105t-5c1fe21dec0f6c023898311e87b12a9f954cd0f442a4a891e67d43e2ce2d4fec3
PageCount 5
ParticipantIDs ieee_primary_7074156
PublicationCentury 2000
PublicationDate 2011-Aug.
PublicationDateYYYYMMDD 2011-08-01
PublicationDate_xml – month: 08
  year: 2011
  text: 2011-Aug.
PublicationDecade 2010
PublicationTitle 2011 19th European Signal Processing Conference
PublicationTitleAbbrev EUSIPCO
PublicationYear 2011
Publisher IEEE
Publisher_xml – name: IEEE
SSID ssib028087106
ssib025355106
Score 1.5188015
Snippet A new lossy compression scheme for distributed and sparse sources under a low complexity encoding constraint is proposed. This architecture is able to exploit...
SourceID ieee
SourceType Publisher
StartPage 422
SubjectTerms Correlation
Decoding
Distortion measurement
Encoding
Joints
Quantization (signal)
Silicon
Title Lossy compression of distributed sparse sources: A practical scheme
URI https://ieeexplore.ieee.org/document/7074156
WOSCitedRecordID wos000377963100086&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3LSgMxFL20xYUrlVZ8k4VLo5NMJsm4k2JxIaULhe5KJrmBgk6lL_DvTTJtVXDjLmQTchNycu7rAFxLL5m0hlGWG6SiKjKqdYXU6dw4X3nkViexCTUc6vG4HLXgZlcLg4gp-Qxv4zDF8t3MrqKr7E4l_JNtaCslm1qt7d3hRQDOHxFDrrNABZK0Jg9UnYYHofgloJLwY3Dwv5UPofddiEdGO4g5ghbWXeg_B2D7JDEZvElircnMExc74EbxKnQkvBLzBZLGMb-4Jw9kUwxl3khgs_iOPXgdPL70n-hGC4FOww9oSQvLgt2YQ5t5aSPQljpnDLWqGDelLwthXeaF4EYYXTKUyok8WBq5Ex5tfgydelbjCRCrjQ8swqJRVmgrtQufuKyqsODOBLJ8Ct1ogMlH0-5istn72d_T57C_dbNm7AI6y_kKL2HPrpfTxfwqndEXevWVGA
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3LSgMxFL3UKuhKpRXfZuHS6CSTmcm4k2KpWEsXFbormeQGCjotfQj-vUmmrQpu3IVsQm5CTs59HYDr1KYs1YpRFiukokgiKmWB1MhYGVtY5FoGsYms15PDYd6vwc2mFgYRQ_IZ3vphiOWbiV56V9ldFvAv3YLtRAgeVdVa69vDEwedP2KGXEaODARxTe7IOnVPQvJLQiUgSHv_f2sfQPO7FI_0NyBzCDUsG9DqOmj7JD4dvEpjLcnEEuN74Hr5KjTEvROzOZLKNT-_Jw9kVQ6l3ojjs_iOTXhtPw5aHbpSQ6Bj9wda0EQzZzlmUEc21R5qcxkzhjIrGFe5zROhTWSdYZRQMmeYZkbEztbIjbCo4yOol5MSj4FoqazjERpVpoXUqTTuGxcVBSbcKEeXT6DhDTCaVg0vRqu9n_49fQW7ncFLd9R96j2fwd7a6Rqxc6gvZku8gB39sRjPZ5fhvL4AbNeYXw
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=proceeding&rft.title=2011+19th+European+Signal+Processing+Conference&rft.atitle=Lossy+compression+of+distributed+sparse+sources%3A+A+practical+scheme&rft.au=Coluccia%2C+G.&rft.au=Magli%2C+E.&rft.au=Roumy%2C+A.&rft.au=Toto-Zarasoa%2C+V.&rft.date=2011-08-01&rft.pub=IEEE&rft.issn=2076-1465&rft.spage=422&rft.epage=426&rft.externalDocID=7074156
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2076-1465&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2076-1465&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2076-1465&client=summon