By Topic

A fast parallel projection algorithm for set theoretic image recovery

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)
Combettes, P.L. ; Dept. of Electr. Eng., City Univ. of New York, NY, USA ; Puh, H.

A new projection algorithm for convex set theoretic image recovery [reconstruction and restoration] is presented. This algorithm comprises all serial and parallel projection methods as particular cases and is straightforwardly implementable on concurrent processors. It proceeds by taking convex combinations of selected projections at each iteration and allows extrapolated relaxations far beyond the range [0,2] used in conventional algorithms. These extrapolated, iteration-dependent relaxations result in very fast convergence. Numerical results are provided which show that the proposed algorithm outperforms existing ones, in particular the popular cyclic method of projections onto convex sets [POCS]

Published in:

Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on  (Volume:v )

Date of Conference:

19-22 Apr 1994