'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
Abstract
The use of wavelets in the image processing domain is still in its
infancy, and largely associated with image compression. With
the advent of the dual-tree hypercomplex wavelet transform (DHWT)
and its improved shift invariance and directional selectivity,
applications in other areas of image processing are more
conceivable. This paper discusses the problems and solutions in
developing the DHWT and its inverse. It also offers a practical
implementation of the algorithms involved. The aim of this work
is to apply the DHWT in machine vision.
Tentative work on a possible new way of feature extraction is
presented. The paper shows that 2-D hypercomplex basis wavelets
can be used to generate steerable filters which allow rotation
as well as translation.</p
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