VLDB 2026 Research / reviewers in the wild / expert
Xide Li
dblp:188/9514
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2020
0000-0003-1441-0409ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Image and video processing · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational science and engineering · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Image and video processing › image restoration
image deblurring |
0.4 | 1 | 2020 | Scanning Imaging Restoration of Moving or Dynamically Deforming Objects · IEEE Trans. Image Process. 2020 |
Image and video processing
image restoration |
0.4 | 1 | 2020 | Scanning Imaging Restoration of Moving or Dynamically Deforming Objects · IEEE Trans. Image Process. 2020 |
Image and video processing › image restoration › image deblurring
motion deblurring |
0.4 | 1 | 2020 | Scanning Imaging Restoration of Moving or Dynamically Deforming Objects · IEEE Trans. Image Process. 2020 |
Computational science and engineering › materials science
materials characterization |
0.1 | 1 | 2020 | Scanning Imaging Restoration of Moving or Dynamically Deforming Objects · IEEE Trans. Image Process. 2020 |
Methods — techniques the papers use, named apart from their topics
point spread function modeling · 0.9inverse restoration · 0.9interpolation · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Scanning Imaging Restoration of Moving or Dynamically Deforming ObjectsabstractThe raster scanning imaging mode is widely used in scanning electron microscopes (SEMs), transmission electron microscopes (TEM), and atomic force microscopes (AFM), and can achieve subatomic resolution. However, only a point on the shallow surface of an object can be imaged at one time using the raster scanning imaging mode, whereas the entire surface of the object can be imaged in the image plane once and instantaneously using the optical imaging mode, which is a parallel imaging mode. Therefore, the image distortion and blur for the scanning imaging mode are different from the optical imaging. In this paper, we propose a theory to describe the mechanism of the scanning imaging process and restore the degraded image (distorted and blurred image) obtained using an SEM. The theory consists of a scanning equation, motion or deformation equations, and an assumption called the intensity-invariant hypothesis. Numerical simulations of the scanning imaging process and restoration of the degraded images are performed using the scanning imaging formulas, spatial non-uniform point spread function, and inverse restoration algorithms, including algebraic, interpolation, and their hybrid methods to verify the feasibility of our theory. In situ experiments on uniform linear motion, uniaxial tensile, and fatigue were also conducted to demonstrate the validity and efficiency of the proposed scanning imaging theory and restoration methods. We anticipate that this imaging and restoration theory will enable the scanning imaging mode to be used in in situ dynamic imaging and for mechanical property measurement of materials. Hongfu Xie, Jiecun Liang, Minghui Liao, Xide Li |
IEEE Trans. Image Process. | 5 |