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URN: urn:nbn:de:bsz:25-opus-2093
URL: http://www.freidok.uni-freiburg.de/volltexte/209/


Wagner, Marcel

Video coding with adaptive vector quantization and rate distortion optimization

Videokodierung mit adaptiver Vektorquantisierung und Raten/Fehler Optimierung

Dokument1.pdf (1.169 KB) (md5sum: 1857422c03f80684a52ed6ac1600f796)

Kurzfassung in Deutsch

The object of this dissertation is to investigate
rate-distortion optimization and to evaluate the prospects of adaptive
vector quantization for digital video compression.
Rate-distortion optimization aims to improve compression performance
using discrete optimization algorithms. We first describe and classify
algorithms that have been developed in the literature to date.
One algorithms is extended in order to make it generally applicable; the correctness of this new procedure is proven. Moreover, we compare the complexity of the aforesaid algorithms, first
implementation-independent and then by run-time experiments.
Finally, we propose a technique to speed up one of the aforementioned algorithms.
Adaptive vector quantization enables adaption to sources with unknown or non-stationary statistics. This feature is important for digital
video data since the statistics of two subsequent
frames is usually similar, but in the long run the general statistics of
frames may change even if scene changes are neglected.
We examine combinations of adaptive vector quantization with various state-of-the-art video compression techniques.
First we present an adaptive vector quantization based codec that is able to encode and decode in real-time using current PC technology. This codec is rate-distortion optimized and adaptive vector quantization is applied in
the wavelet transform domain. The organization of the wavelet coefficients is then made more efficient using adaptive partition techniques. Moreover, the main adaptability mechanism of adaptive vector quantization, the so-called codebook update, is studied.
Finally, a combination of adaptive vector quantization and motion compensation is taken into consideration. We show that for very low bitrates adaptive vector quantization performs on prediction
residual frames better or at least as well as discrete cosine transform coding.


SWD-Schlagwörter: Vektorquantisierung , Kodierung , Optimierung/Nebenbedingung , Datenverdichtung
Freie Schlagwörter (deutsch): Videocodierung
Freie Schlagwörter (englisch): Vector quantization , Rate/Distortion optimization , video coding
CCS Klassifikation I.4.2 Comp
Institut: Institut für Informatik
Fakultät: Fakultät für Angewandte Wissenschaften (bis Sept. 2002)
DDC-Sachgruppe: Informatik
Dokumentart: Dissertation
Erstgutachter: Saupe, Dietmar (Prof. Dr.)
Sprache: Englisch
Tag der mündlichen Prüfung: 02.10.2000
Erstellungsjahr: 2000
Publikationsdatum: 19.07.2001
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