By Topic

A Coding-Cost Framework for Super-Resolution Motion Layer Decomposition

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)
Schoenemann, T. ; Centre for Math. Sci., Lund Univ., Lund, Sweden ; Cremers, D.

We consider the problem of decomposing a video sequence into a superposition of (a given number of) moving layers. For this problem, we propose an energy minimization approach based on the coding cost. Our contributions affect both the model (what is minimized) and the algorithmic side (how it is minimized). The novelty of the coding-cost model is the inclusion of a refined model of the image formation process, known as super resolution. This accounts for camera blur and area averaging arising in a physically plausible image formation process. It allows us to extract sharp high-resolution layers from the video sequence. The algorithmic framework is based on an alternating minimization scheme and includes the following innovations. (1) A video labeling, we optimize the layer domains. This allows to regularize the shapes of the layers and a very elegant handling of occlusions. (2) We present an efficient parallel algorithm for extracting super-resolved layers based on TV filtering.

Published in:

Image Processing, IEEE Transactions on  (Volume:21 ,  Issue: 3 )