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 to edge detection over geometrical images and over industrial data are shown.

A new class of non-separable symmetric wavelets for image processing

COTRONEI, Mariantonia;
2009

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 to edge detection over geometrical images and over industrial data are shown.
Symmetry; Wavelets; Edge detection
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/5334
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