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open-access-imgOpen AccessSimple accurate model‐based phase diversity phase retrieval algorithm for wavefront sensing in high‐resolution optical imaging systems
Qin Shun,
Zhang Yongbing,
Wang Haoqian,
Chan Wai Kin
Publication year2020
Publication title
iet image processing
Resource typeJournals
PublisherThe Institution of Engineering and Technology
In optical imaging systems, the aberration is an important factor that impedes realising diffraction‐limited imaging. Accurate wavefront sensing and control play important role in modern high‐resolution optical imaging systems nowadays. In this study, a simple model‐based phase retrieval algorithm is proposed for accurate efficient wavefront sensing with high dynamic range. In the authors’ algorithm, a wavefront is represented by the Zernike polynomials, and the Zernike coefficients are solved by the least‐squares‐based non‐linear optimisation method, i.e. the Lederberg–Marquardt algorithm, with multiple phase‐diversity images. The numerical results show that the proposed algorithm is capable of retrieving wavefront with a large dynamic range up to seven wavelength and robust to noise. In comparison, the proposed algorithm is more efficient than the existing model‐based technique and more accurate than existing Fourier ‐ transformation‐based iterative techniques.
Subject(s)adaptive optics , algorithm , artificial intelligence , computer science , epistemology , fourier transform , image (mathematics) , optics , phase (matter) , phase retrieval , philosophy , physics , quantum mechanics , resolution (logic) , simple (philosophy) , simple algorithm , superresolution , thermodynamics , wavefront
SCImago Journal Rank0.401

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