Zobrazit v EDS

Regularized Compression of A Noisy Blurred Image

Uloženo v:
Podrobná bibliografie
Název: Regularized Compression of A Noisy Blurred Image
Autoři: Paola Favati, Grazia Lotti, Ornella Menchi, Francesco Romani
Informace o vydavateli: Zenodo
Rok vydání: 2016
Sbírka: Zenodo
Témata: Image Regularization, Image Compression, Nonnegative Matrix Factorization
Popis: Both regularization and compression are important issues in image processing and have been widely approached in the literature. The usual procedure to obtain the compression of an image given through a noisy blur requires two steps: first a deblurring step of the image and then a factorization step of the regularized image to get an approximation in terms of low rank nonnegative factors. We examine here the possibility of swapping the two steps by deblurring directly the noisy factors or partially denoised factors. The experimentation shows that in this way images with comparable regularized compression can be obtained with a lower computational cost.
Druh dokumentu: article in journal/newspaper
Jazyk: unknown
Relation: https://zenodo.org/records/2869756; oai:zenodo.org:2869756; https://doi.org/10.5281/zenodo.2869756
DOI: 10.5281/zenodo.2869756
Dostupnost: https://doi.org/10.5281/zenodo.2869756
https://zenodo.org/records/2869756
Rights: Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode
Přístupové číslo: edsbas.686B6E8E
Databáze: BASE
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://doi.org/10.5281/zenodo.2869756#
    Name: EDS - BASE (s4221598)
    Category: fullText
    Text: View record from BASE
  – Url: https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=EBSCO&SrcAuth=EBSCO&DestApp=WOS&ServiceName=TransferToWoS&DestLinkType=GeneralSearchSummary&Func=Links&author=Favati%20P
    Name: ISI
    Category: fullText
    Text: Nájsť tento článok vo Web of Science
    Icon: https://imagesrvr.epnet.com/ls/20docs.gif
    MouseOverText: Nájsť tento článok vo Web of Science
Header DbId: edsbas
DbLabel: BASE
An: edsbas.686B6E8E
RelevancyScore: 863
AccessLevel: 3
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 863.477478027344
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Regularized Compression of A Noisy Blurred Image
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Paola+Favati%22">Paola Favati</searchLink><br /><searchLink fieldCode="AR" term="%22Grazia+Lotti%22">Grazia Lotti</searchLink><br /><searchLink fieldCode="AR" term="%22Ornella+Menchi%22">Ornella Menchi</searchLink><br /><searchLink fieldCode="AR" term="%22Francesco+Romani%22">Francesco Romani</searchLink>
– Name: Publisher
  Label: Publisher Information
  Group: PubInfo
  Data: Zenodo
– Name: DatePubCY
  Label: Publication Year
  Group: Date
  Data: 2016
– Name: Subset
  Label: Collection
  Group: HoldingsInfo
  Data: Zenodo
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Image+Regularization%22">Image Regularization</searchLink><br /><searchLink fieldCode="DE" term="%22Image+Compression%22">Image Compression</searchLink><br /><searchLink fieldCode="DE" term="%22Nonnegative+Matrix+Factorization%22">Nonnegative Matrix Factorization</searchLink>
– Name: Abstract
  Label: Description
  Group: Ab
  Data: Both regularization and compression are important issues in image processing and have been widely approached in the literature. The usual procedure to obtain the compression of an image given through a noisy blur requires two steps: first a deblurring step of the image and then a factorization step of the regularized image to get an approximation in terms of low rank nonnegative factors. We examine here the possibility of swapping the two steps by deblurring directly the noisy factors or partially denoised factors. The experimentation shows that in this way images with comparable regularized compression can be obtained with a lower computational cost.
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: article in journal/newspaper
– Name: Language
  Label: Language
  Group: Lang
  Data: unknown
– Name: NoteTitleSource
  Label: Relation
  Group: SrcInfo
  Data: https://zenodo.org/records/2869756; oai:zenodo.org:2869756; https://doi.org/10.5281/zenodo.2869756
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.5281/zenodo.2869756
– Name: URL
  Label: Availability
  Group: URL
  Data: https://doi.org/10.5281/zenodo.2869756<br />https://zenodo.org/records/2869756
– Name: Copyright
  Label: Rights
  Group: Cpyrght
  Data: Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode
– Name: AN
  Label: Accession Number
  Group: ID
  Data: edsbas.686B6E8E
PLink https://erproxy.cvtisr.sk/sfx/access?url=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.686B6E8E
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.5281/zenodo.2869756
    Languages:
      – Text: unknown
    Subjects:
      – SubjectFull: Image Regularization
        Type: general
      – SubjectFull: Image Compression
        Type: general
      – SubjectFull: Nonnegative Matrix Factorization
        Type: general
    Titles:
      – TitleFull: Regularized Compression of A Noisy Blurred Image
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Paola Favati
      – PersonEntity:
          Name:
            NameFull: Grazia Lotti
      – PersonEntity:
          Name:
            NameFull: Ornella Menchi
      – PersonEntity:
          Name:
            NameFull: Francesco Romani
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2016
          Identifiers:
            – Type: issn-locals
              Value: edsbas
            – Type: issn-locals
              Value: edsbas.oa
ResultId 1