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A unified approach for constructing a large class of multiwavelets is presented. This class includes Geronimo-Hardin-Massopust (1994), Alpert (1993), finite element and Daubechies-like multiwavelets. The approach is based on the characterisation of approximation order of r multiscaling functions using a known compactly supported refinable super-function. The characterisation is formulated as a generalised eigenvalue equation. The generalised left eigenvectors of the finite down-sampled convolution matrix Lf give the coefficients in the finite linear combination of multiscaling functions that produce the desired super-function. The unified approach based on the super-function theory can be used to construct new multiwavelets with short support, high approximation order and symmetry.
Vision, Image and Signal Processing, IEE Proceedings - (Volume:150 , Issue: 3 )
Date of Publication: 20 June 2003