Resumen:
|
Image compression is of great importance in multimedia systems and
applications because it drastically reduces bandwidth requirements for
transmission and memory requirements for storage. Although earlier
standards for ...[+]
Image compression is of great importance in multimedia systems and
applications because it drastically reduces bandwidth requirements for
transmission and memory requirements for storage. Although earlier
standards for image compression were based on the Discrete Cosine
Transform (DCT), a recently developed mathematical technique, called
Discrete Wavelet Transform (DWT), has been found to be more efficient
for image coding.
Despite improvements in compression efficiency, wavelet image coders
significantly increase memory usage and complexity when compared with
DCT-based coders. A major reason for the high memory requirements is
that the usual algorithm to compute the wavelet transform requires the
entire image to be in memory. Although some proposals reduce the memory
usage, they present problems that hinder their implementation. In
addition, some wavelet image coders, like SPIHT (which has become a
benchmark for wavelet coding), always need to hold the entire image in
memory.
Regarding the complexity of the coders, SPIHT can be considered quite
complex because it performs bit-plane coding with multiple image scans.
The wavelet-based JPEG 2000 standard is still more complex because it
improves coding efficiency through time-consuming methods, such as an
iterative optimization algorithm based on the Lagrange multiplier
method, and high-order context modeling.
In this thesis, we aim to reduce memory usage and complexity in
wavelet-based image coding, while preserving compression efficiency. To
this end, a run-length encoder and a tree-based wavelet encoder are
proposed. In addition, a new algorithm to efficiently compute the
wavelet transform is presented. This algorithm achieves low memory
consumption using line-by-line processing, and it employs recursion to
automatically place the order in which the wavelet transform is
computed, solving some synchronization problems that have not been
tackled by previous proposals. The proposed encode
[-]
|