Universal Lossless Source Coding Techniques for Images and Short Data Sequences

Nicklas Ekstrand

Universal Lossless Source Coding Techniques for Images and Short Data Sequences

Nicklas Ekstrand

Institutionen för elektro- och informationsteknik

Forskningsoutput: Avhandling › Doktorsavhandling (monografi)

Sammanfattning

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.

Originalspråk	engelska
Kvalifikation	Doktor
Tilldelande institution	Institutionen för elektro- och informationsteknik
Handledare	[unknown], [unknown], handledare, Extern person
Tilldelningsdatum	2001 apr. 6
Förlag	Department of Information Technology, Lund Univeristy
ISBN (tryckt)	91-7167-020-3
Status	Published - 2001

Bibliografisk information

Defence details

Date: 2001-04-06
Time: 10:15
Place: E-building E:1406

External reviewer(s)

Name: Willems, Frans
Title: [unknown]
Affiliation: [unknown]

---

Ämnesklassifikation (UKÄ)

Elektroteknik och elektronik

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@phdthesis{d555989ad3ac436c835b91a6a4b1a736,

title = "Universal Lossless Source Coding Techniques for Images and Short Data Sequences",

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 data sequences. The presented techniques can be used separately or together when designing efficient lossless data compression systems.",

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",

author = "Nicklas Ekstrand",

note = "Defence details Date: 2001-04-06 Time: 10:15 Place: E-building E:1406 External reviewer(s) Name: Willems, Frans Title: [unknown] Affiliation: [unknown] ---",

year = "2001",

language = "English",

isbn = "91-7167-020-3",

publisher = "Department of Information Technology, Lund Univeristy",

type = "Doctoral Thesis (monograph)",

school = "Department of Electrical and Information Technology",

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TY - THES

T1 - Universal Lossless Source Coding Techniques for Images and Short Data Sequences

AU - Ekstrand, Nicklas

N1 - Defence details Date: 2001-04-06 Time: 10:15 Place: E-building E:1406 External reviewer(s) Name: Willems, Frans Title: [unknown] Affiliation: [unknown] ---

PY - 2001

Y1 - 2001

N2 - 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.

AB - 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.

KW - CMF

KW - PPA

KW - linear prediction

KW - prediction

KW - local optimization

KW - JPEG

KW - context tree weighting

KW - lossless image compression

KW - Source coding

KW - universal source coding

KW - ARQ

KW - Electronics and Electrical technology

KW - Elektronik och elektroteknik

KW - Imaging

KW - image processing

KW - Bildbehandling

M3 - Doctoral Thesis (monograph)

SN - 91-7167-020-3

PB - Department of Information Technology, Lund Univeristy

ER -

Universal Lossless Source Coding Techniques for Images and Short Data Sequences

Sammanfattning

Bibliografisk information

Ämnesklassifikation (UKÄ)

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