Omnidirectionally Balanced Multiwavelets for Vector Wavelet Transforms
DCC '02 Proceedings of the Data Compression Conference
Some properties and construction of multiwavelets related to different symmetric centers
Mathematics and Computers in Simulation
A multivariate thresholding technique for image denoising using multiwavelets
EURASIP Journal on Applied Signal Processing
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This paper describes a basic difference between multiwavelets and scalar wavelets that explains, without using zero moment properties, why certain complications arise in the implementation of discrete multiwavelet transforms. Assuming we wish to avoid the use of prefilters in implementing the discrete multiwavelet transform, it is suggested that the behavior of the iterated filter bank associated with a multiwavelet basis of multiplicity r is more fully revealed by an expanded set of r2 scaling functions φi,j. This paper also introduces new K-balanced orthogonal multiwavelet bases based on symmetric FIR filters. The nonlinear design equations arising in this work are solved using the Grobner basis. The minimal-length K-balanced multiwavelet bases based on even-length symmetric FIR filters are better behaved than those based on odd-length symmetric FIR filters, as illustrated by special relations they satisfy and by examples constructed