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Universal Lossless Source Coding Techniques for Images and Short Data Sequences

Ekstrand, Nicklas LU (2001)
Abstract (Swedish)
Popular Abstract in Swedish

Denna avhandling behandlar olika metoder för datakompression och speciellt metoder som är lämpliga för komprimering av digitala bilder. Avsikten med datakompressionen är att finna en representation av den ursprungliga datan (tex en bild) som upptar mindre plats på tex ett skivminne.
Abstract
In this thesis various topics in universal lossless source coding are discussed and analyzed. The main focus in this work is on lossless data compression of grayscale still images. Such images are, for example, frequently occurring in medical imaging.



Based on theoretical considerations and empirical observations new compression algorithms are presented that are, in terms of compression performance, efficient compared to traditional methods.



This work includes research on how to use the Context Tree Weighting algorithm, linear prediction and probability assignment techniques in lossless data compression. The performance of these algorithms/methods is studied both asymptotically and for usage on short... (More)
In this thesis various topics in universal lossless source coding are discussed and analyzed. The main focus in this work is on lossless data compression of grayscale still images. Such images are, for example, frequently occurring in medical imaging.



Based on theoretical considerations and empirical observations new compression algorithms are presented that are, in terms of compression performance, efficient compared to traditional methods.



This work includes research on how to use the Context Tree Weighting algorithm, linear prediction and probability assignment techniques in lossless data compression. The performance of these algorithms/methods is studied both asymptotically and for usage on short data sequences.



The presented techniques can be used separately or together when designing efficient lossless data compression systems. (Less)
Please use this url to cite or link to this publication:
author
opponent
  • Willems, Frans
organization
publishing date
type
Thesis
publication status
published
subject
keywords
CMF, PPA, linear prediction, prediction, local optimization, JPEG, context tree weighting, lossless image compression, Source coding, universal source coding, ARQ, Electronics and Electrical technology, Elektronik och elektroteknik, Imaging, image processing, Bildbehandling
pages
132 pages
publisher
Department of Information Technology, Lund Univeristy
defense location
E-building E:1406
defense date
2001-04-06 10:15
external identifiers
  • Other:ISRN: LUTEDX/TEIT-01/1017-SE
ISBN
91-7167-020-3
language
English
LU publication?
no
id
d555989a-d3ac-436c-835b-91a6a4b1a736 (old id 20364)
date added to LUP
2007-05-28 08:41:49
date last changed
2016-09-19 08:45:03
@misc{d555989a-d3ac-436c-835b-91a6a4b1a736,
  abstract     = {In this thesis various topics in universal lossless source coding are discussed and analyzed. The main focus in this work is on lossless data compression of grayscale still images. Such images are, for example, frequently occurring in medical imaging.<br/><br>
<br/><br>
Based on theoretical considerations and empirical observations new compression algorithms are presented that are, in terms of compression performance, efficient compared to traditional methods.<br/><br>
<br/><br>
This work includes research on how to use the Context Tree Weighting algorithm, linear prediction and probability assignment techniques in lossless data compression. The performance of these algorithms/methods is studied both asymptotically and for usage on short data sequences.<br/><br>
<br/><br>
The presented techniques can be used separately or together when designing efficient lossless data compression systems.},
  author       = {Ekstrand, Nicklas},
  isbn         = {91-7167-020-3},
  keyword      = {CMF,PPA,linear prediction,prediction,local optimization,JPEG,context tree weighting,lossless image compression,Source coding,universal source coding,ARQ,Electronics and Electrical technology,Elektronik och elektroteknik,Imaging,image processing,Bildbehandling},
  language     = {eng},
  pages        = {132},
  publisher    = {ARRAY(0xc965920)},
  title        = {Universal Lossless Source Coding Techniques for Images and Short Data Sequences},
  year         = {2001},
}