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Metaheuristics are employed for the solution of th e p ase unwrapping problem (for 3D object reconstruction) by the branch cuts method, posed as an analogous of the traveling salesman problem, which is an NP-hard decision problem. The metaheuristic algorithms carry out a globa l se rch for the optimal configuration of the so-called branch cuts which corre sponds to a pairing of discontinuities with opposed sign in the wrapped phase ma p. Three representative algorithms of different metaheuristic families are comp ared: discrete Particle Swarm Optimization (from bioinspired algorithms), Genetic Algorithms (from evolutionary algorithms) and a novel Estimation of Distr ibution Algorithm presented in this work that follows a Multinomial distributio n. These metaheuristics are comparatively evaluated according to the quality of the solutions achieved, execution time and computational cost, with the aim of building a robust and automated algorithm competitive against traditional met hods.

Phase Unwrapping for 3D Object Reconstruction by means of Population-based Metaheuristics