Regular Articles

Reduced-complexity multiview prediction scheme with content-adaptive disparity vector estimation

[+] Author Affiliations
Aykut Avci, Jelle De Smet

Ghent University, Department of Electronics and Information Systems, Centre for Microsystems Technology, Technologiepark 914, 9052 Ghent, Belgium

Jan De Cock, Peter Lambert

Ghent University-IBBT, Department of Electronics and Information Systems, Multimedia Laboratory, Gaston Crommenlaan 8 bus 201, B-9050 Ledeberg-Ghent, Belgium

Youri Meuret

Vrije Universiteit Brussel, Department of Applied Physics and Photonics, Brussels Photonics Team Pleinlaan 2, 1050 Brussels, Belgium

Herbert De Smet

Ghent University, Department of Electronics and Information Systems, Centre for Microsystems Technology, Technologiepark 914, 9052 Ghent, Belgium

imec-Cmst, Technologiepark 914, 9052 Ghent, Belgium

J. Electron. Imaging. 21(3), 033009 (Aug 22, 2012). doi:10.1117/1.JEI.21.3.033009
History: Received January 13, 2012; Revised May 15, 2012; Accepted June 14, 2012
Text Size: A A A

Abstract.  Disparity estimation is a highly complex and time consuming process in multiview video encoders. Since multiple views taken from a two-dimensional camera array need to be coded at every time instance, the complexity of the encoder plays an important role besides its rate-distortion performance. In previous papers we have introduced a new frame type called the D (derived) frame that exploits the strong geometrical correspondence between views, thereby reducing the complexity of the encoder. By employing the D frames instead of some of the P frames in the prediction structure, significant complexity gain can be achieved if the threshold value, which is a keystone element to adjust the complexity at the cost of quality and/or bit-rate, is selected wisely. A new adaptive method to calculate the threshold value automatically from existing information during the encoding process is presented. In this method, the threshold values are generated for each block of each D frame to increase the accuracy. The algorithm is applied to several image sets and 20.6% complexity gain is achieved using the automatically generated threshold values without compromising quality or bit-rate.

Figures in this Article
© 2012 SPIE and IS&T

Citation

Aykut Avci ; Jan De Cock ; Jelle De Smet ; Youri Meuret ; Peter Lambert, et al.
"Reduced-complexity multiview prediction scheme with content-adaptive disparity vector estimation", J. Electron. Imaging. 21(3), 033009 (Aug 22, 2012). ; http://dx.doi.org/10.1117/1.JEI.21.3.033009


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.