Title: | Improved Error Reduction and Hybrid Input Output Algorithms for Phase Retrieval by including a Sparse Dictionary Learning-Based Inpainting Method |
Authors: | Su, Jian-Jia Tien, Chung-Hao 光電工程學系 Department of Photonics |
Issue Date: | 20-Jul-2020 |
Abstract: | The phase retrieval (PR), reconstructing an object from its Fourier magnitudes, is equivalent to a nonlinear inverse problem. In this paper, we proposed a two-step algorithm that traditional ER/HIO iteration plays as the coarse feature reconstruction, whereas the KSVD-based inpainting technique deals with the fine feature set accordingly. Since the KSVD allows the content of oversampled dictionary with sparse representation to adaptively fit a given set of object examples, as long as the ER/HIO algorithms provide decent object estimation at early stage, the pixels violating the object constraint can be restored with superior image quality. The numerical analyses demonstrated the effectiveness of ER + KSVD and HIO + KSVD through multiple independent initial Fourier phases. With its versatility and simplicity, the proposed method can be generalized to be implemented with more PR state-of-the-arts. |
URI: | http://dx.doi.org/10.1155/2020/3481830 http://hdl.handle.net/11536/155113 |
ISSN: | 1687-9384 |
DOI: | 10.1155/2020/3481830 |
Journal: | INTERNATIONAL JOURNAL OF OPTICS |
Volume: | 2020 |
Begin Page: | 0 |
End Page: | 0 |
Appears in Collections: | Articles |