Open AccessPhase retrieval of pure phase object based on compressed sensing
Author(s) -
Zhen-ya Yang,
Cao Zheng
Publication year - 2013
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.62.104203
Subject(s) - phase retrieval , phase (matter) , computer science , sampling (signal processing) , piecewise , compressed sensing , algorithm , fourier transform , intensity (physics) , nyquist–shannon sampling theorem , amplitude , object (grammar) , optics , computer vision , artificial intelligence , mathematics , detector , physics , telecommunications , mathematical analysis , quantum mechanics
Traditional phase retrieval algorithm, which iteratively reconstructs the phase from 2-intensity measurement or 1-intensity measurement, requires Shannon sampling theorem to be satisfied. This could lead to more requirements for data storage when high resolution imaging is concerned. In order to lower the sampling budget, in this paper we purpose a compressed sensing based phase retrieval algorithm. Through 1-intensity measurement in Fourier plane, our improved Hybrid I/O algorithm is used to reconstruct the exact phase retribution of pure phase object. The algorighm proposed in this paper can reconstruct piecewise regular phase distributed pure phase object from far less amplitude measurements than ones for which the sampling theorem requires to be satisfied. The simulated data indicate that the algorithm has a good converge performance.