A growing percentage of the world population now uses image and video coding technologies on a regular basis. These technologies are behind the success and quick deployment of services and products such as digital pictures, digital television, DVDs, and Internet video communications. Today’s digital video coding paradigm represented by the ITU-T and MPEG standards mainly relies on a hybrid of block- based transform and interframe predictive coding approaches. In this coding framework, the encoder architecture has the task to exploit both the temporal and spatial redundancies present in the video sequence, which is a rather complex exercise. As a consequence, all standard video encoders have a much higher computational complexity than the decoder (typically five to ten times more complex), mainly due to the temporal correlation exploitation tools, notably the motion estimation process. This type of architecture is well-suited for applications where the video is encoded once and decoded many times, i.e., one-to-many topologies, such as broadcasting or video-on-demand, where the cost of the decoder is more critical than the cost of the encoder. Distributed source coding (DSC) has emerged as an enabling technology for sensor networks. It refers to the compression of correlated signals captured by different sensors that do not communicate between themselves. All the signals captured are compressed independently and transmitted to a central base station, which has the capability to decode them jointly. Tutorials on distributed source coding for sensor networks, presenting the underlying theory as well as first practical solutions, have already been published in IEEE Signal Processing Magazine in 2002 [1] and 2004 [2]. Video compression has been recast into a distributed source coding framework, leading to distributed video coding (DVC) systems targeting low coding complexity and error resilience. A comprehensive survey of first DVC solutions can be found in [3]. While, for sake of completeness, basics about DSC are reviewed, this article focuses on DVC latest developments for both monoview and multiview set-ups.

Distributed Monoview and Multiview Video Coding

LEONARDI, Riccardo;
2007-01-01

Abstract

A growing percentage of the world population now uses image and video coding technologies on a regular basis. These technologies are behind the success and quick deployment of services and products such as digital pictures, digital television, DVDs, and Internet video communications. Today’s digital video coding paradigm represented by the ITU-T and MPEG standards mainly relies on a hybrid of block- based transform and interframe predictive coding approaches. In this coding framework, the encoder architecture has the task to exploit both the temporal and spatial redundancies present in the video sequence, which is a rather complex exercise. As a consequence, all standard video encoders have a much higher computational complexity than the decoder (typically five to ten times more complex), mainly due to the temporal correlation exploitation tools, notably the motion estimation process. This type of architecture is well-suited for applications where the video is encoded once and decoded many times, i.e., one-to-many topologies, such as broadcasting or video-on-demand, where the cost of the decoder is more critical than the cost of the encoder. Distributed source coding (DSC) has emerged as an enabling technology for sensor networks. It refers to the compression of correlated signals captured by different sensors that do not communicate between themselves. All the signals captured are compressed independently and transmitted to a central base station, which has the capability to decode them jointly. Tutorials on distributed source coding for sensor networks, presenting the underlying theory as well as first practical solutions, have already been published in IEEE Signal Processing Magazine in 2002 [1] and 2004 [2]. Video compression has been recast into a distributed source coding framework, leading to distributed video coding (DVC) systems targeting low coding complexity and error resilience. A comprehensive survey of first DVC solutions can be found in [3]. While, for sake of completeness, basics about DSC are reviewed, this article focuses on DVC latest developments for both monoview and multiview set-ups.
File in questo prodotto:
File Dimensione Formato  
GPTELO_2007_SPM.pdf

gestori archivio

Tipologia: Full Text
Licenza: DRM non definito
Dimensione 1.24 MB
Formato Adobe PDF
1.24 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
GPTELO_SPM-2007_pre-print.pdf

accesso aperto

Descrizione: GPTELO_SPM-2007_pre-print
Tipologia: Documento in Pre-print
Licenza: Creative commons
Dimensione 1.71 MB
Formato Adobe PDF
1.71 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/18191
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 144
  • ???jsp.display-item.citation.isi??? 105
social impact