Comparison of the efficiency of deterministic and stochastic algorithms for visual reconstruction

Author

Blake, Andrew

Author_Institution

Dept. of Comput. Sci., Edinburgh Univ., UK

Volume

11

Issue

1

fYear

1989

fDate

1/1/1989 12:00:00 AM

Firstpage

2

Lastpage

12

Abstract

Piecewise continuous reconstruction of real-valued data can be formulated in terms of nonconvex optimization problems. Both stochastic and deterministic algorithms have been devised to solve them. The simplest such reconstruction process is the weak string. Exact solutions can be obtained for it and are used to determine the success or failure of the algorithms under precisely controlled conditions. It is concluded that the deterministic algorithm (graduated nonconvexity) outstrips stochastic (simulated annealing) algorithms both in computational efficiency and in problem-solving power

Keywords

computer vision; computerised picture processing; optimisation; computational efficiency; deterministic algorithms; nonconvex optimization; problem-solving power; stochastic algorithms; visual reconstruction; weak string; Biomembranes; Computational modeling; Computer science; Glands; Image motion analysis; Noise reduction; Problem-solving; Simulated annealing; Stochastic processes; Testing;

fLanguage

English

Journal_Title

Pattern Analysis and Machine Intelligence, IEEE Transactions on

Publisher

ieee

ISSN

0162-8828

Type

jour

DOI

10.1109/34.23109

Filename

23109