Demo Data from EDBT 2026 / reviewers in the wild / expert
Bingtai Liu
dblp:174/7954
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2016
—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 coding · 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 coding › image compression
wavelet-based image coding |
0.2 | 1 | 2016 | Generalization of SPIHT: Set Partition Coding System · IEEE Trans. Image Process. 2016 |
Methods — techniques the papers use, named apart from their topics
generalized tree · 0.2degree-k SPIHT · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | Generalization of SPIHT: Set Partition Coding SystemabstractThis paper constructs a set partition coding system (SPACS) to combine the advantages of different types of set partition coding algorithms. General tree (GT) is an important conception introduced in this paper, which can represent tree set and square set simultaneously. With the help of GT, SPIHT is generalized to construct degree- k SPIHT based on the analysis of two kinds of set partition operations. Using the same coding mechanism, SPACS (k,p) is constructed, aided with virtual subbands that are generated by recursive division on the LL band. SPACS belongs to tree-set partition coding algorithms if k and p take smaller values. In particular, SPACS(2,1) is the classical SPIHT. SPACS tends toward a block-set partition coding algorithm as k,p increases. Location bit, amplitude bit, and unnecessary bit are presented, which can be used to analyze the coding efficiency of SPACS. We compress 256 images with 512×512 using SPACS. The numerical results show SPACS achieves some improvements in coding efficiency over SPIHT, especially at very low bitrate. On average, to code every image, SPACS(3,1) (at an average of 3.93 bpp) needs 7792 more location bits but saves 10 218 unnecessary bits, compared with SPIHT (3.94 bpp). Qiufu Li, Derong Chen, Bingtai Liu, Jiulu Gong |
IEEE Trans. Image Process. | 4 |