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Diego Dugatkin

dblp:33/3550 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2004
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 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.

Theoretical computer science
1 paper
Coding theory · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Coding theory › source coding › scalable source coding
multiresolution source coding
0.012004
Multiresolution vector quantization · IEEE Trans. Inf. Theory 2004
Coding theory
source coding
0.012004
Multiresolution vector quantization · IEEE Trans. Inf. Theory 2004
Coding theory › source coding › quantization
vector quantization
0.012004
Multiresolution vector quantization · IEEE Trans. Inf. Theory 2004
YearPublicationVenuePosition
2004 Multiresolution vector quantization
abstract
Multiresolution source codes are data compression algorithms yielding embedded source descriptions. The decoder of a multiresolution code can build a source reproduction by decoding the embedded bit stream in part or in whole. All decoding procedures start at the beginning of the binary source description and decode some fraction of that string. Decoding a small portion of the binary string gives a low-resolution reproduction; decoding more yields a higher resolution reproduction; and so on. Multiresolution vector quantizers are block multiresolution source codes. This paper introduces algorithms for designing fixed- and variable-rate multiresolution vector quantizers. Experiments on synthetic data demonstrate performance close to the theoretical performance limit. Experiments on natural images demonstrate performance improvements of up to 8 dB over tree-structured vector quantizers. Some of the lessons learned through multiresolution vector quantizer design lend insight into the design of more sophisticated multiresolution codes.
Michelle Effros, Diego Dugatkin
IEEE Trans. Inf. Theory2