Unsupervised deep learning method for single image super-resolution of the thick pinhole imaging system using deep image prior
Thick pinhole imaging system is widely used for diagnosing intense pulsed radiation sources. However, owing to the trade-off among spatial resolution, field of view (FOV) and signal-to-noise ratio (SNR), the imaging system normally falls short in achieving high-precision spatial diagnosis. In this p...
Saved in:
Main Authors: | Guoguang Li, Liang Sheng, Baojun Duan, Yang Li, Dongwei Hei, Qingzi Xing |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-01-01
|
Series: | Nuclear Engineering and Technology |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1738573324003863 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Unsupervised Hyperspectral Denoising Based on Deep Image Prior and Least Favorable Distribution
by: Keivan Faghih Niresi, et al.
Published: (2022-01-01) -
Deep Joint Demosaicking and Super-Resolution for Spectral Filter Array Images
by: Abdelhamid N. Fsian, et al.
Published: (2025-01-01) -
Enhancing the Spatial Resolution of Sentinel-2 Images Through Super-Resolution Using Transformer-Based Deep-Learning Models
by: Alireza Sharifi, et al.
Published: (2025-01-01) -
Accurate recognition of micromorphology images of epoxy coatings for deep-sea environments based on a deep learning super-resolution method
by: JiaQi Pan, et al.
Published: (2025-09-01) -
Non-Rigid Cycle Consistent Bidirectional Network with Transformer for Unsupervised Deformable Functional Magnetic Resonance Imaging Registration
by: Yingying Wang, et al.
Published: (2025-01-01)