Simple accurate model‐based phase diversity phase retrieval algorithm for wavefront sensing in high‐resolution optical imaging systems

Abstract

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.

Optimized Approach for Image Design Processing in Optical Networks: A Comparative Study

“…Inspired by the method of phase difference [63], reference [64] used pairs of in-focus and out-offocus light-intensity images as training data and used the Zernike coefficient of wavefront aberration as a label to train a CNN for WFSless AO system control. The data flow of the model is shown in The CNN model adopted is modified from the well-known AlexNet [65] 2. Three training data sets are used to train CNN separately, and three models with different parameters are obtained.…”