Demo Data from VLDB 2026 / reviewers in the wild / expert
Justin S. McMichael
dblp:06/3120
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2003
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 2
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 coding · 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 coding
JPEG compression |
0.0 | 1 | 2003 | Recompression of JPEG images by requantization · IEEE Trans. Image Process. 2003 |
Image and video coding
perceptual quality optimization |
0.0 | 1 | 2003 | Recompression of JPEG images by requantization · IEEE Trans. Image Process. 2003 |
Image and video coding › quantization
requantization |
0.0 | 1 | 2003 | Recompression of JPEG images by requantization · IEEE Trans. Image Process. 2003 |
Methods — techniques the papers use, named apart from their topics
laplacian distribution modeling · 0.0discrete cosine transform analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2003 | Recompression of JPEG images by requantizationabstractIn this paper, we report a novel heuristic for requantizing JPEG images. The resulting images are generally smaller and often have improved perceptual image quality over a "blind" requantization approach, that is, one that does not consider the properties of the quantization matrices. The heuristic is supported by a detailed mathematical treatment which incorporates the well-known Laplacian distribution of the AC discrete cosine transform (DCT) coefficients with an analysis of the error introduced by requantization. We note that the technique is applicable to any image compression method which employs discrete cosine transforms and quantization. Heinz H. Bauschke, Chris H. Hamilton, Mason S. Macklem, Justin S. McMichael, Nicholas R. Swart |
IEEE Trans. Image Process. | 4 |
| 2002 | A requantization-based method for recompressing JPEG imagesabstractWe propose a new method for requantizing JPEG images, based on the well-known Laplacian distribution of the AC discrete cosine transform (DCT) coefficients and on an analysis of the error introduced by requantization. The resulting images have improved perceptual image quality over a “blind” requantization approach, that is, one that does not consider the properties of the quantization matrices. Heinz H. Bauschke, Chris H. Hamilton, Mason S. Macklem, Justin S. McMichael, Nicholas R. Swart |
ICASSP | 4 |