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G. Mohammad-Khani

dblp:97/851 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2006
—ORCID · none

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

Computer networks · 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.

Theoretical computer science
1 paper
Coding theory · 100%
Computer graphics and multimedia
1 paper
Image and video coding · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video coding
entropy coding
0.012006
Simplification of VLC Tables With Application to ML and MAP Decoding Algorithms · IEEE Trans. Commun. 2006
Image and video coding › entropy coding
variable-length coding
0.012006
Simplification of VLC Tables With Application to ML and MAP Decoding Algorithms · IEEE Trans. Commun. 2006

Methods — techniques the papers use, named apart from their topics

trellis-based decoding · 0.1soft decoding · 0.1
YearPublicationVenuePosition
2006 Simplification of VLC Tables With Application to ML and MAP Decoding Algorithms
abstract
Many source coding standards (JPEG, H263+, H264), rely heavily on entropy coding with variable-length codes (VLC). However, bitstreams made of VLC-encoded data are particularly sensitive to transmission errors. Recent results tend to use knowledge of the VLC structure in order to perform an efficient decoding of the bitstream. These techniques use a trellis describing the structure of the VLC codebook and assume that some a priori information is available at decoder side. Significant improvements, compared with prefix decoding of bitstreams are achieved. However, the complexity of these techniques may become intractable when realistic VLC codebooks are considered. This paper presents an algorithm for compacting VLC tables. The codewords are grouped into a minimum number of classes. Decoding algorithms may then work on a reduced number of classes, instead of working on the whole set of codewords. A proof of optimality is provided for the VLC table-compaction algorithm. The algorithm is applied to the H263+ VLC codebook and merges the 204 codewords into 25 classes. The resulting compact tables are shown to be exactly equivalent to the initial ones when used with hard decoding algorithms. The properties of the associated soft decoding algorithms using these compact tables are also evaluated.
G. Mohammad-Khani, Chang-Ming Lee, Michel Kieffer, Pierre Duhamel
IEEE Trans. Commun.1