Improved Error Reduction and Hybrid Input Output Algorithms for Phase Retrieval by including a Sparse Dictionary Learning-Based Inpainting Method
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 deal...
Saved in:
Main Authors: | Jian-Jia Su, Chung-Hao Tien |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2020-01-01
|
Series: | International Journal of Optics |
Online Access: | http://dx.doi.org/10.1155/2020/3481830 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Error-Mask-Adaptive Dynamic Filtering for Image Inpainting
by: Keunsoo Ko, et al.
Published: (2025-01-01) -
Dictionary-Based, Clustered Sparse Representation for Hyperspectral Image Classification
by: Zhen-tao Qin, et al.
Published: (2015-01-01) -
Compounds in dictionary-based Cross-language information retrieval_revised
Published: (2002-01-01) -
Incoherent dictionary learning and sparse representation for single-image rain removal
by: Hong-zhong TANG, et al.
Published: (2017-07-01) -
Image retrieval based on the feature of VLAD and sparse representation
by: Wen YAN, et al.
Published: (2016-12-01)