Abstract
Phase retrieval (PR) is a kind of ill-condition inverse problem which can be found in various applications. Based on the Wirtinger flow (WF) method, a reweighted Wirtinger flow (RWF) method is proposed to deal with the PR problem. In a nutshell, RWF searches the global optimum by solving a series of sub-PR problems with changing weights. Theoretical analyses illustrate that the RWF has a geometric convergence from a deliberate initialization when the weights are bounded by 1 and . Numerical tests also show the RWF has a lower sampling complexity compared with the WF. As an essentially adaptive truncated Wirtinger flow (TWF) method, the RWF performs better than the TWF especially when the ratio between sampling number and length of signal is small.
© 2017 Optical Society of America
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