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New Weighting Alternatives to MCFN Phase Unwrapping

Nurjannah Syakrani, Edy Tri Baskoro, Tati L. Mengko, A.B. Suksmono


A minimum cost flow on a network (MCFN) based phase unwrapping is one of the most popular phase unwrapping methods. This approach employs a weighting function in order to minimize residue. In this paper, we propose to use both of magnitude or phase images, and kernel based correlation to define a weighting function. Besides, we also propose a new method based on an adaptive Shannon kernel which shows a competitive performance. The Fringe-Zero-Crossing Metric (FZX) of this weighting approach is less than 6%.


Phase unwrapping, magnitude image, weighting, Shannon entropy kernel, FZX.

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