Demo Data from VLDB 2026 / reviewers in the wild / expert
Michael B. Martin
dblp:43/172
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2001
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author
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
image compression |
0.0 | 1 | 2001 | New image compression techniques using multiwavelets and multiwavelet packets · IEEE Trans. Image Process. 2001 |
Image and video coding › image compression
wavelet-based image coding |
0.0 | 1 | 2001 | New image compression techniques using multiwavelets and multiwavelet packets · IEEE Trans. Image Process. 2001 |
Image and video coding
transform coding |
0.0 | 1 | 2001 | New image compression techniques using multiwavelets and multiwavelet packets · IEEE Trans. Image Process. 2001 |
Methods — techniques the papers use, named apart from their topics
quantization · 0.0multiwavelet transform · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2001 | New image compression techniques using multiwavelets and multiwavelet packetsabstractAdvances in wavelet transforms and quantization methods have produced algorithms capable of surpassing the existing image compression standards like the Joint Photographic Experts Group (JPEG) algorithm. For best performance in image compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry. However, the design possibilities for wavelets are limited because they cannot simultaneously possess all of the desirable properties. The relatively new field of multiwavelets shows promise in obviating some of the limitations of wavelets. Multiwavelets offer more design options and are able to combine several desirable transform features. The few previously published results of multiwavelet-based image compression have mostly fallen short of the performance enjoyed by the current wavelet algorithms. This paper presents new multiwavelet transform and quantization methods and introduces multiwavelet packets. Extensive experimental results demonstrate that our techniques exhibit performance equal to, or in several cases superior to, the current wavelet filters. Michael B. Martin, Amy E. Bell |
IEEE Trans. Image Process. | 1 |