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Hugh Emberson

dblp:321/9817 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1994
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 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 · 91% Multimedia systems and quality of experience · 9%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video coding › image compression
bilevel image coding
0.011994
Textual image compression: two-stage lossy/lossless encoding of textual images · Proc. IEEE 1994
Image and video coding › entropy coding
context-based entropy coding
0.011994
Textual image compression: two-stage lossy/lossless encoding of textual images · Proc. IEEE 1994
Image and video coding › image compression
lossless image compression
0.011994
Textual image compression: two-stage lossy/lossless encoding of textual images · Proc. IEEE 1994
Multimedia systems and quality of experience › image transmission
progressive transmission
0.011994
Textual image compression: two-stage lossy/lossless encoding of textual images · Proc. IEEE 1994
YearPublicationVenuePosition
1994 Textual image compression: two-stage lossy/lossless encoding of textual images
abstract
A two-stage method for compressing bilevel images is described that is particularly effective for images containing repeated subimages, notably text. In the first stage, connected groups of pixels, corresponding approximately to individual characters, are extracted from the image. These are matched against an adaptively constructed library of patterns seen so far, and the resulting sequence of symbol identification numbers is coded and transmitted. From this information, along with the library itself and the offset from one mark to the next, an approximate image can be reconstructed. The result is a lossy method of compression that outperforms other schemes. The second stage employs the reconstructed image as an aid for encoding the original image using a statistical context-based compression technique. This yields a total bandwidth for exact transmission appreciably undercutting that required by other lossless binary image compression methods. Taken together, the lossy, and lossless methods provide an effective two-stage progressive transmission capability for textual images which has application for legal, medical, and historical purposes, and to archiving in general.>
Ian H. Witten, Timothy C. Bell, Hugh Emberson, Stuart Inglis, Alistair Moffat
Proc. IEEE3