Please use this identifier to cite or link to this item: https://doi.org/10.1117/12.2020382
Title: Ensemble of hybrid genetic algorithm for two-dimensional phase unwrapping
Authors: Balakrishnan, D.
Quan, C. 
Tay, C.J. 
Keywords: Artificial intelligence
Branch-cut method
Ensemble
Hybrid genetic algorithm
Phase unwrapping
Issue Date: 2013
Source: Balakrishnan, D., Quan, C., Tay, C.J. (2013). Ensemble of hybrid genetic algorithm for two-dimensional phase unwrapping. Proceedings of SPIE - The International Society for Optical Engineering 8769 : -. ScholarBank@NUS Repository. https://doi.org/10.1117/12.2020382
Abstract: The phase unwrapping is the final and trickiest step in any phase retrieval technique. Phase unwrapping by artificial intelligence methods (optimization algorithms) such as hybrid genetic algorithm, reverse simulated annealing, particle swarm optimization, minimum cost matching showed better results than conventional phase unwrapping methods. In this paper, Ensemble of hybrid genetic algorithm with parallel populations is proposed to solve the branch-cut phase unwrapping problem. In a single populated hybrid genetic algorithm, the selection, cross-over and mutation operators are applied to obtain new population in every generation. The parameters and choice of operators will affect the performance of the hybrid genetic algorithm. The ensemble of hybrid genetic algorithm will facilitate to have different parameters set and different choice of operators simultaneously. Each population will use different set of parameters and the offspring of each population will compete against the offspring of all other populations, which use different set of parameters. The effectiveness of proposed algorithm is demonstrated by phase unwrapping examples and advantages of the proposed method are discussed. © 2013 SPIE.
Source Title: Proceedings of SPIE - The International Society for Optical Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/73436
ISBN: 9780819495679
ISSN: 0277786X
DOI: 10.1117/12.2020382
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