A New Class of Non-Separable Symmetric Wavelets for Image Processing

Guido Andaloro, Mariantonia Cotronei, Luigia Puccio


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


Symmetry, wavelets, edge detection.

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DOI: http://dx.doi.org/10.1685/

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