Demo Data from EDBT 2026 / reviewers in the wild / expert
Shih-Tung Wu
dblp:99/4752
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2005
—ORCID · none
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% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Image and video processing › image restoration › inverse problem
inverse halftoning |
0.1 | 1 | 2005 | Inverse Halftoning Algorithm Using Edge-Based Lookup Table Approach · IEEE Trans. Image Process. 2005 |
Methods — techniques the papers use, named apart from their topics
lookup table · 0.1edge classification · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2005 | Inverse Halftoning Algorithm Using Edge-Based Lookup Table ApproachabstractThe inverse halftoning algorithm is used to reconstruct a gray image from an input halftone image. Based on the recently published lookup table (LUT) technique, this paper presents a novel edge-based LUT method for inverse halftoning which improves the quality of the reconstructed gray image. The proposed method first uses the LUT-based inverse halftoning method as a preprocessing step to transform the given halftone image to a base gray image, and then the edges are extracted and classified from the base gray image. According to these classified edges, a novel edge-based LUT is built up to reconstruct the gray image. Based on a set of 30 real training images with both low-and high-frequency contents, experimental results demonstrated that the proposed method achieves a better image quality when compared to the currently published two methods, by Chang et al. and Meşe and Vaidyanathan. Kuo-Liang Chung, Shih-Tung Wu |
IEEE Trans. Image Process. | 2 |