Abstract
In this paper, we propose the Variance Reduced Randomized Kaczmarz (VR-RK) algorithm for XFEL signal particle imaging phase retrieval. The VR-RK algorithm is inspired by the randomized Kaczmarz algorithm and the variance reduction in stochastic gradient methods. The formulations of the VR-RK algorithm under the L 1 and L 2 constraints are also presented. Numerical simulations demonstrate that the VR-RK method has a faster convergence rate compared with the randomized Kaczmarz method. Tests on the synthetic signal particle imaging data and the PR772 XFEL real imaging data show that the VR-RK algorithm can recover information with higher accuracy. It is useful for biological data processing.
| Original language | English |
|---|---|
| Title of host publication | 2022 IEEE International Conference on Image Processing (ICIP) |
| Publisher | IEEE |
| Pages | 3186-3190 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781665496209 |
| ISBN (Print) | 9781665496216 |
| DOIs | |
| Publication status | Published - 16 Oct 2022 |
| Event | 2022 IEEE International Conference on Image Processing, ICIP 2022 - Bordeaux, France Duration: 16 Oct 2022 → 19 Oct 2022 https://ieeexplore.ieee.org/xpl/conhome/9897158/proceeding |
Publication series
| Name | IEEE International Conference on Image Processing |
|---|---|
| ISSN (Print) | 1522-4880 |
| ISSN (Electronic) | 2381-8549 |
Conference
| Conference | 2022 IEEE International Conference on Image Processing, ICIP 2022 |
|---|---|
| Country/Territory | France |
| City | Bordeaux |
| Period | 16/10/22 → 19/10/22 |
| Internet address |
User-Defined Keywords
- Phase retrieval
- randomized Kaczmarz
- stochastic optimization
- variance reduction
- XFEL single particle imaging