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Two-dimensional minimum discontinuity phase unwrapping based on tabu search

Phase unwrapping is the task of recovering the true phase values, given the wrapped phase values in an image. Flynn's minimum discontinuity phase unwrapping algorithm can deal with many different kinds of phase unwrapping problems successfully. However, since it takes the whole wrapped phase image as the improving loop search areas, Flynn's algorithm has low efficiency in searching for the phase's discontinuity. To overcome this drawback, a new minimum discontinuity phase unwrapping algorithm based on tabu search is proposed in this paper. In the proposed algorithm, the nodes of the wrapped image are divided into different N levels according to the corresponding quality of the wrapped image and the nodes with high levels are added into tabu list. In the iteration process of improving loops search, the tabu list is updated according to the aspiration criterion to allow the search areas extend to nodes with high levels. By this means, it searches the highest probability nodes belonging to paths of improving loops first and the lowest probability nodes last. As a result, it significantly improves the efficiency of the algorithm. The proposed algorithm is described in detail and verified by use of an experimental wrapped phase image with noise and undersampling. Unwrapped results show that the proposed algorithm works well and is more effectively than the Flynn's minimum discontinuity algorithm.