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

It is known that wavelet analysis is a powerful mathematical tool for image process-
ing. 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 them-
selves 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 to edge detection over geometrical images and over industrial data
are shown.