By Topic

Temporal Video Denoising Based on Multihypothesis Motion Compensation

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
$33 $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

4 Author(s)
Liwei Guo ; Hong Kong Univ. of Sci. & Technol., Clear Water Bay ; Oscar C. Au ; Mengyao Ma ; Zhiqin Liang

Denoising module is required by any practical video processing systems. Most existing denoising schemes are spatio-temporal filters which operate on data over three dimensions. However, to limit the number of inputs, these filters only utilize one reference frame and cannot fully exploit temporal correlation. In this paper, a recursive temporal denoising filter named multihypothesis motion compensated filter (MHMCF) is proposed. To fully exploit temporal correlation, MHMCF performs motion estimation in a number of reference frames to construct multiple hypotheses (temporal predictions) of the current pixel. These hypotheses are combined by weighted averaging to suppress noise and estimate the actual current pixel value. Based on the multihypothesis motion compensated residue model presented in this paper, we investigate the efficiency of MHMCF, and some numerical evaluations are revealed. Experimental results show that MHMCF demonstrates quite good denoising performance while the inputs are much fewer than spatio-temporal filters. Moreover, as a purely temporal filter, it can well preserve spatial details and achieve satisfactory visual quality.

Published in:

IEEE Transactions on Circuits and Systems for Video Technology  (Volume:17 ,  Issue: 10 )