View in EDS

Automatic and optimal hierarchical quantizer decomposition to build knowledge for video transmission.

Saved in:
Bibliographic Details
Title: Automatic and optimal hierarchical quantizer decomposition to build knowledge for video transmission.
Authors: Rosa Rodriguez-Sa´nchez, Jose A. Garci´a, Joaqui´n Fdez-Valdivia, Antonio Garrido
Source: Optical Engineering. Oct2007, Vol. 46 Issue 10, p10740-10740. 1p.
Subjects: Mathematical decomposition, Decomposition method, Videos, Video compression
Abstract: Current video encoding methods base their decisions (which sequence of bits must be sent at each instant t) on a single knowledge base throughout all transmission times (in most cases, the knowledge is based on energy values, so coefficients with higher energy are prioritized over to those with lower energy). This way, there are no mechanisms working simultaneously with, or in parallel with, the transmission process and imposing the need to modify the knowledge base in accordance with the requirements of the transmission process (sending the information that will produce the best possible quality per bit transmitted). Since the knowledge base is conceived statically (it does not change over time), there will come a time when all information to be transmitted is of equal relevance, even though there may still be differences in that information. Based on this reasoning, we propose a video compression method with automatic internal mechanisms that make it possible to specify a knowledge base (containing the optimal sequences to be sent for each quantizer) at each instant of the transmission process. The methodology is based on a hierarchical quantizer decomposition. In the first level we have quantizers with an high linear velocity, and in the second level, quantizers with high energy. We automatically select the best decomposition by minimizing the cost of coding the information. Comparisons with the state of the art in video coding show the advantages of the approach. [ABSTRACT FROM AUTHOR]
Copyright of Optical Engineering is the property of SPIE - International Society of Optical Engineering and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 27415028
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Automatic and optimal hierarchical quantizer decomposition to build knowledge for video transmission.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Rosa+Rodriguez-Sa´nchez%22">Rosa Rodriguez-Sa´nchez</searchLink><br /><searchLink fieldCode="AR" term="%22Jose+A%2E+Garci´a%22">Jose A. Garci´a</searchLink><br /><searchLink fieldCode="AR" term="%22Joaqui´n+Fdez-Valdivia%22">Joaqui´n Fdez-Valdivia</searchLink><br /><searchLink fieldCode="AR" term="%22Antonio+Garrido%22">Antonio Garrido</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Optical+Engineering%22">Optical Engineering</searchLink>. Oct2007, Vol. 46 Issue 10, p10740-10740. 1p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Mathematical+decomposition%22">Mathematical decomposition</searchLink><br /><searchLink fieldCode="DE" term="%22Decomposition+method%22">Decomposition method</searchLink><br /><searchLink fieldCode="DE" term="%22Videos%22">Videos</searchLink><br /><searchLink fieldCode="DE" term="%22Video+compression%22">Video compression</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Current video encoding methods base their decisions (which sequence of bits must be sent at each instant t) on a single knowledge base throughout all transmission times (in most cases, the knowledge is based on energy values, so coefficients with higher energy are prioritized over to those with lower energy). This way, there are no mechanisms working simultaneously with, or in parallel with, the transmission process and imposing the need to modify the knowledge base in accordance with the requirements of the transmission process (sending the information that will produce the best possible quality per bit transmitted). Since the knowledge base is conceived statically (it does not change over time), there will come a time when all information to be transmitted is of equal relevance, even though there may still be differences in that information. Based on this reasoning, we propose a video compression method with automatic internal mechanisms that make it possible to specify a knowledge base (containing the optimal sequences to be sent for each quantizer) at each instant of the transmission process. The methodology is based on a hierarchical quantizer decomposition. In the first level we have quantizers with an high linear velocity, and in the second level, quantizers with high energy. We automatically select the best decomposition by minimizing the cost of coding the information. Comparisons with the state of the art in video coding show the advantages of the approach. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Optical Engineering is the property of SPIE - International Society of Optical Engineering and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=27415028
RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 1
        StartPage: 10740
    Subjects:
      – SubjectFull: Mathematical decomposition
        Type: general
      – SubjectFull: Decomposition method
        Type: general
      – SubjectFull: Videos
        Type: general
      – SubjectFull: Video compression
        Type: general
    Titles:
      – TitleFull: Automatic and optimal hierarchical quantizer decomposition to build knowledge for video transmission.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Rosa Rodriguez-Sa´nchez
      – PersonEntity:
          Name:
            NameFull: Jose A. Garci´a
      – PersonEntity:
          Name:
            NameFull: Joaqui´n Fdez-Valdivia
      – PersonEntity:
          Name:
            NameFull: Antonio Garrido
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 10
              Text: Oct2007
              Type: published
              Y: 2007
          Identifiers:
            – Type: issn-print
              Value: 00913286
          Numbering:
            – Type: volume
              Value: 46
            – Type: issue
              Value: 10
          Titles:
            – TitleFull: Optical Engineering
              Type: main
ResultId 1