Demo Data from EDBT 2026 / reviewers in the wild / expert
Dongbin Shi
dblp:72/5823
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2007
—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 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Image and video processing › image enhancement › contrast enhancement
histogram specification |
0.1 | 1 | 2007 | Joint Exact Histogram Specification and Image Enhancement Through the Wavelet Transform · IEEE Trans. Image Process. 2007 |
Image and video processing
image enhancement |
0.1 | 1 | 2007 | Joint Exact Histogram Specification and Image Enhancement Through the Wavelet Transform · IEEE Trans. Image Process. 2007 |
Image and video processing
wavelet transform |
0.0 | 1 | 2007 | Joint Exact Histogram Specification and Image Enhancement Through the Wavelet Transform · IEEE Trans. Image Process. 2007 |
Methods — techniques the papers use, named apart from their topics
wavelet transform · 0.1pixel ordering · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2007 | Joint Exact Histogram Specification and Image Enhancement Through the Wavelet TransformabstractHistogram specification (equalization) is an important tool for tasks such as image enhancement and normalization. Although this problem has exact solution for continuous images, in the case of digital images, it is ill posed. Recently, an exact pixel ordering method based solely on local image intensity was proposed, yet still with some limitations, especially since it ignores the important image edge information. In this paper, we present a wavelet-based method that simultaneously achieves the exact histogram specification and good image enhancement performance. It does so through a carefully designed strict pixel ordering process, during which the wavelet coefficients are fine tuned for the image enhancement purpose. Compared to previous work, this approach takes into account not only local mean intensity values, but also local edge information. Other advantages include fast pixel ordering, good statistical models, and better image enhancement performance. Experimental results and comparison with state-of-the-art methods are presented. Yi Wan 0003, Dongbin Shi |
IEEE Trans. Image Process. | 2 |