By Topic

Hash-Based Motion Modeling in Wyner-Ziv Video Coding

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Tagliasacchi, M. ; Dipt. di Elettronica e Informazione, Politecnico di Milano, Milan, Italy ; Tubaro, S.

Generally, distributed video coding (DVC) schemes perform motion estimation at the decoder side, without the current frame being available. In order to generate the side-information reliably, one solution consists in allocating a limited bit budget to send a hash of the current frame. At the decoder, this auxiliary hash is used to perform motion estimation. This paper studies the accuracy of hash-based motion estimation and compares it to conventional encoder-side motion estimation. We show that, at low rates, the very limited bit-budget of the hash does not ensure a reliable motion estimation, while at medium to high rates the motion accuracy is comparable with the finite precision used to represent motion vectors. Then, we derive the rate-distortion characteristic, which combines the cost of encoding the hash and the prediction residuals after decoder-side motion compensation. We show that, at high rates, hash-based motion modeling can virtually achieve the same coding efficiency as motion-compensated predictive coding. Instead, at medium-to-low rates we observe a significant coding loss. Experimental results on real video sequences validate the results of the proposed model.

Published in:

Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on  (Volume:1 )

Date of Conference:

15-20 April 2007