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Keith A. Birney

dblp:33/2237 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1995
—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 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video coding › quantization
entropy-constrained quantization		 0.011995
On the modeling of DCT and subband image data for compression · IEEE Trans. Image Process. 1995
Image and video coding
transform coding		 0.011995
On the modeling of DCT and subband image data for compression · IEEE Trans. Image Process. 1995
Image and video coding › transform coding
discrete cosine transform		 0.011995
On the modeling of DCT and subband image data for compression · IEEE Trans. Image Process. 1995
Image and video coding › scalable coding
pyramid coding		 0.011995
On the modeling of DCT and subband image data for compression · IEEE Trans. Image Process. 1995
Image and video coding › transform coding
subband coding		 0.011995
On the modeling of DCT and subband image data for compression · IEEE Trans. Image Process. 1995

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

laplacian modeling · 0.0generalized gaussian modeling · 0.0
YearPublicationVenuePosition
1995 On the modeling of DCT and subband image data for compression
abstract
Image subband and discrete cosine transform coefficients are modeled for efficient quantization and noiseless coding. Quantizers and codes are selected based on Laplacian, fixed generalized Gaussian, and adaptive generalized Gaussian models. The quantizers and codes based on the adaptive generalized Gaussian models are always superior in mean-squared error distortion performance but, generally, by no more than 0.08 bit/pixel, compared with the much simpler Laplacian model-based quantizers and noiseless codes. This provides strong motivation for the selection of pyramid codes for transform and subband image coding.
Keith A. Birney, Thomas R. Fischer
 IEEE Trans. Image Process.1