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	Two-dimensional phase unwrapping using semidefinite relaxation
	Xiao, Jin-Jun ; Luo, Zhi-Quan ; Jiang, Ming
	2009
英文摘要	In many imaging applications, the continuous phase information of the measured signal is wrapped to a single period of 2??, resulting in phase ambiguity. In this paper we consider the two-dimensional phase unwrapping problem and propose a Maximum a Posteriori (MAP) framework for estimating the true phase values based on the wrapped phase data. In particular, assuming a joint Gaussian prior on the original phase image, we show that the MAP formulation leads to a binary quadratic minimization problem. The latter can be efficiently solved by semidefinite relaxation (SDR). We compare the performances of our proposed method with the existing L1/L2-norm minimization approaches. The numerical results demonstrate that the SDR approach significantly outperforms the existing phase unwrapping methods. ?2009 IEEE.; EI; 0
语种	英语
出处	EI
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/263120]
专题	数学科学学院
推荐引用方式 GB/T 7714	Xiao, Jin-Jun,Luo, Zhi-Quan,Jiang, Ming. Two-dimensional phase unwrapping using semidefinite relaxation. 2009-01-01.

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