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Thamas Fischer

dblp:165/3622 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1987
—ORCID · none

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

Computer networks · 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 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video coding › predictive coding
differential pulse code modulation
0.011987
Transform and Hybrid Transform/DPCM Coding of Images Using Pyramid Vector Quantization · IEEE Trans. Commun. 1987
Image and video coding › video compression
hybrid coding
0.011987
Transform and Hybrid Transform/DPCM Coding of Images Using Pyramid Vector Quantization · IEEE Trans. Commun. 1987
Image and video coding › quantization › vector quantization
pyramid vector quantization
0.011987
Transform and Hybrid Transform/DPCM Coding of Images Using Pyramid Vector Quantization · IEEE Trans. Commun. 1987
Image and video coding
transform coding
0.011987
Transform and Hybrid Transform/DPCM Coding of Images Using Pyramid Vector Quantization · IEEE Trans. Commun. 1987
Image and video coding
image compression
0.011987
Transform and Hybrid Transform/DPCM Coding of Images Using Pyramid Vector Quantization · IEEE Trans. Commun. 1987

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

rate assignment · 0.0mean squared error analysis · 0.0
YearPublicationVenuePosition
1987 Transform and Hybrid Transform/DPCM Coding of Images Using Pyramid Vector Quantization
abstract
The transform and hybrid transform/DPCM methods of image coding are generalized to allow pyramid vector quantization of the transform coefficients. An asymptotic mean-squared error performance expression is derived for the pyramid vector quantizer and used to determine the optimum rate assignment for encoding the various transform coefficients. Coding simulations for two images at average rates of 0.5-1 bit/pixel demonstrate a 1-3 dB improvement in signal-to-noise ratio for the vector quantization approach in the hybrid coding, with more modest improvements in signal-to-noise ratio in the transform coding. However, this improvement is quite noticeable in image quality, particularly in reducing "blockiness" in the low bit rate encoded images.
Huey-Chen Tseng, Thamas Fischer
IEEE Trans. Commun.2