http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
On the tree-based embedded subband image coding
xii, 107 leaves : illustrations ; 28 cm.
This research develops innovative coding principles combined
with new tree structures to advance the embedded tree coding
technology. Embedded tree coding schemes, such as embedded
zerotrees and spatial orientation trees, are among the most
successful wavelet-based image compression techniques. These
schemes are developed on the basis of the self-similarity of
wavelet coefficients across different subbands. Despite
their excellent performance, existing embedded tree coders
are only applicable to square images, and the coefficient
bits at different spatial locations are evenly interlaced in
the encoded bit stream. To code any size of rectangular
images, we propose an efficient inter-band mapping algorithm,
the Generalized Self-Similarity Tree (GST). For intra-band
image coding, we propose a new coding scheme, the compact
quadtree (CQT). The proposed schemes are shown to outperform
existing embedded tree coding methods in the literature. As
an application of the CQT, a selective compression of medical
images based on regions of interest (ROIS) is designed. We
characterize the spatial similarity, that is the similarity
of adjacent wavelet coefficients in a subband, and show that
that this property plays an important role in the design of
embedded tree coding schemes. To optimize the transmission
sequence of wavelet coefficients for progressive visual
communications, new methods are designed and analyzed.
Issued also on microfiche from University Microfilms Inc.
Includes bibliographical references: pages 103-106.