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Sparse superresolution phase retrieval from phase-coded noisy intensity patterns

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Original languageEnglish
Article number094103
JournalOptical Engineering
Issue number9
Publication statusPublished - 1 Sep 2017
Publication typeA1 Journal article-refereed


We consider a computational superresolution inverse diffraction problem for phase retrieval from phase-coded intensity observations. The optical setup includes a thin lens and a spatial light modulator for phase coding. The designed algorithm is targeted on an optimal solution for Poissonian noisy observations. One of the essential instruments of this design is a complex-domain sparsity applied for complex-valued object (phase and amplitude) to be reconstructed. Simulation experiments demonstrate that good quality imaging can be achieved for high-level of the superresolution with a factor of 32, which means that the pixel of the reconstructed object is 32 times smaller than the sensor's pixel. This superresolution corresponds to the object pixel as small as a quarter of the wavelength.


  • complex-domain sparsity, discrete optical signal processing, phase imaging, phase retrieval, superresolution

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Field of science, Statistics Finland