By Topic

An optimal neuron evolution algorithm for constrained quadratic programming in image restoration

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

1 Author(s)
Ling Guan ; Dept. of Electr. Eng., Sydney Univ., NSW, Australia

An optimal neuron evolution algorithm for the restoration of linearly distorted images is presented in this paper. The proposed algorithm is motivated by the symmetric positive-definite quadratic programming structure inherent in restoration. Theoretical analysis and experimental results show that the algorithm not only significantly increases the convergence rate of processing, but also produces good restoration results. In addition, the algorithm provides a genuine parallel processing structure which ensures computationally feasible spatial domain image restoration

Published in:

Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on  (Volume:26 ,  Issue: 4 )