A New Class of Non-Separable Symmetric Wavelets for Image Processing
Abstract
It is known that wavelet analysis is a powerful mathematical tool for image processing.
For such type of applications, symmetry of the wavelet filters is claimed to produce
less visual artifacts than non-linear phase wavelets. On the other hand, the filters themselves
can be separable or non-separable. While separable filters offer the advantage of
low-complexity processing, their non-separable counterparts have more degrees of freedom
and hence allow better designs. In this talk we discuss about new classes of non-separable
wavelet filters with different types of symmetry. A scheme for their construction is given
and some applications of edge detection over geometrical images and over industrial data
are shown.
[DOI: 10.1685/CSC09324] About DOI
For such type of applications, symmetry of the wavelet filters is claimed to produce
less visual artifacts than non-linear phase wavelets. On the other hand, the filters themselves
can be separable or non-separable. While separable filters offer the advantage of
low-complexity processing, their non-separable counterparts have more degrees of freedom
and hence allow better designs. In this talk we discuss about new classes of non-separable
wavelet filters with different types of symmetry. A scheme for their construction is given
and some applications of edge detection over geometrical images and over industrial data
are shown.
[DOI: 10.1685/CSC09324] About DOI
Keywords
Symmetry, wavelets, edge detection.
Full Text:
PDFDOI: https://doi.org/10.1685/
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