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Wavelets have made quite a splash recently in the signal processing
community, especially with regard to applications like compression
(speech, audio, image and video), modeling, and restoration. Until
recently, they have been studied under different names by three different
communities: mathematics, signal processing, and computer vision. This
course will present the recent body of knowledge that has contributed to
a unified understanding of this field, and will describe the relationship
between wavelets, multirate filter banks, and multiresolution analysis studied
in the mathematics, signal processing, and computer vision communities
respectively. The treatment will have a signal processing flavor with
sufficient mathematical rigor. Applications of wavelets to signal
compression, nonlinear signal approximation theory, modeling, denoising,
and restoration, motion analysis and estimation and communications
will be addressed.
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