By Topic

A Robust and Computationally Efficient Simultaneous Super-Resolution Scheme for Image Sequences

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)
Zibetti, M.V.W. ; Fed. Univ. of Santa Catarina, Florianopolis ; Mayer, J.

This work presents a new class of algorithms for super-resolution (SR) of image sequences. This class of algorithms estimates simultaneously all frames of a sequence by employing an iterative minimization of a regularized cost function. Similarly to other SR techniques, the proposed approach exploits the correlation among the frames of the sequence. This correlated information helps to improve the resolution of the captured images. By employing the motion information only in the prior term of the cost function, the proposed method achieves a better fidelity and more robust performance, when compared to other methods. This original approach provides a fidelity equivalent to the obtained by the simultaneous methods, while achieving a lower computational complexity. The isolation of the motion equations in the prior term allows an increased control over the motion errors, and as a consequence, provides an improved robustness. The performance of the proposed method is discussed and compared with other methods in the literature. In the comparative experiments, it is considered both the minimization over the Euclidean norm, which is employed to achieve low computational complexity, and the minimization over the Huber norm or norm, which is used to produce images with sharp edges and higher robustness to large motion errors.

Published in:

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