Multiple Plane Phase Retrieval Based On Inverse Regularized Imaging and Discrete Diffraction Transform
Author(s) -
Artem Migukin,
Vladimir Katkovnik,
Jaakko Astola,
Pramod K. Rastogi,
Erwin Hack
Publication year - 2010
Publication title -
aip conference proceedings
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.177
H-Index - 75
eISSN - 1551-7616
pISSN - 0094-243X
DOI - 10.1063/1.3426172
Subject(s) - phase retrieval , inverse problem , algorithm , inverse , diffraction tomography , angular spectrum method , aliasing , regularization (linguistics) , diffraction , fourier transform , mathematics , computer science , iterative reconstruction , optics , artificial intelligence , mathematical analysis , physics , geometry , undersampling
The phase retrieval is formulated as an inverse problem, where the forward propagation is defined by Discrete Diffraction Transform (DDT) [1], [2]. This propagation model is precise and aliasing free for pixelwise invariant (pixelated) wave field distributions in the sensor and object planes. Because of finite size of sensors DDT can be ill‐conditioned and the regularization is an important component of the inverse. The proposed algorithm is designed for multiple plane observations and can be treated as a generalization of the Gerchberg‐Saxton iterative algorithm. The proposed algorithm is studied by numerical experiments produced for phase and amplitude modulated object distributions. Comparison versus the conventional forward propagation models such as the angular spectrum decomposition and the convolutional model used in the algorithm of the same structure shows a clear advantage of DDT enabling better accuracy and better imaging.
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