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   -> Volume 3, Issue 10


PhD: Image and Video Coding Using a Wavelet Decomposition
 
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herjan@it.et.tudelft.nl (Herjan Barnard)
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PostPosted: Mon Dec 02, 2002 1:09 pm    
Subject: PhD: Image and Video Coding Using a Wavelet Decomposition
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PhD: Image and Video Coding Using a Wavelet Decomposition

PH.D. ABSTRACT

Title: Image and Video Coding Using a Wavelet Decomposition
Author: Herjan J. Barnard
Advisors: Jan Biemond and Jos H. Weber
Institute: Delft University of Technology, The Netherlands

The thesis is available by anonymous ftp:

Site: it.et.tudelft.nl (130.161.145.13)
Login name: anonymous
Directory: /pub/thesis-1994/Barnard

For more information please contact Dr. Weber by E-mail: weber@et.tudelft.nl.


ABSTRACT - "Image and Video Coding Using a Wavelet Decomposition"

The thesis starts with a derivation of the wavelet theory. A consistent
notation and naming for the wavelet theory is presented analogous to the
Fourier theory, depending on the signal being discrete or continuous, and
finite or infinite length. The differences and similarities between the
formulas are shown in a table. The discrete wavelet transform (DWT) is
shown to be equal to a repeated subband decomposition with a two-channel
filter bank. Several diagrams illustrate how the signal extension at the
boundaries of finite length signals should be performed to preserve the
perfect reconstruction property. Further, a method is introduced to
decompose arbitrary length signals into subbands without producing extra
subband samples.
Next, the application of the DWT to image and video coding is considered.
The objective and subjective coding performances of the DWT are compared
for various filters originating from both the subband coding theory and
the wavelet theory. In general, no large differences in coding performance
appear, but the biorthogonal linear phase wavelet filters perform best,
followed by almost all linear phase subband coding filters, and the
non-linear phase wavelet filters. The regularity of a filter seems only to
be important for the synthesis filters, and a regularity order of 2 seems
to be sufficient. Several tables and figures with the characteristics of
all filters under consideration are shown in the appendix. In addition,
improvements of some well-known Johnston filters are suggested.
In the third place, the quincunx 2-D DWT is considered. It is expected to
perform better than the dyadic 2-D DWT for some classes of images, like
aerial photographs and images with many diagonal structures, but in the
experiments the quincunx 2-D DWT shows a lower performance than the dyadic
2-D DWT, both in terms of objective and subjective measures.
Finally, a region-based discrete wavelet transform (RBDWT) is introduced
to code the texture in a region-based image coding scheme. This RBDWT has the
advantage that it enables to distribute the available bit rate over subbands
as well as regions. It differs from other texture coding methods like
polynomial fitting, that the regions should be rather large, while the RBDWT
takes care of the remaining edges inside the regions. Further, the
computational complexity is very low. The implementation is explained in detail,
and an image coding scheme is presented. The coding performance of the RBDWT
is compared to the performance of the standard DWT. The signal-to-noise ratio
is slightly lower, but in terms of subjective visual quality the new method
tends to be better, because of the smaller ringing artefacts and the better
preservation of edges. Therefore, the new RBDWT image coding technique is at
least competitive to the standard DWT. Several suggestions for further
research in this new direction are given.
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