Multiwavelets are a new addition to the body of wavelet theory. Realizable as matrix-valued filterbanks leading to wavelet bases, multiwavelets offer simultaneous orthogonality, symmetry, and short support, which is not possible with scalar two-channel wavelet systems. After reviewing this theory, we examine the use of multiwavelets in a filterbank setting for discrete-time signal and image pro...

Over the past decade wavelet transforms have received a lot of attention from researchers in many diierent areas. Both discrete and continuous wavelet transforms have shown great promises in such diverse elds as image compression, image De-noising, signal processing, computer graphics, and pattern recognition, to name a few. Most of the work has been done on scalar wavelets, i.e., wavelets gene...

We present a study on applications of multiwavelet analysis to image compression, where filter coefficients form matrices. As a multiwavelet filter bank has multiple channels of inputs, we investigate the data initialization problem by considering prefilters and postfilters that may give more efficient representations of the decomposed data. The interpolation postfilter and prefilter are formul...

Orthogonal wavelet bases have recently been developed using multiple mother wavelet functions. Applying the discrete multiple wavelet transform requires the input data to be preprocessed to obtain a more economical decomposition. We discuss the properties of several prepro-cessing methods and their eeect on the thresholding results. We propose a multivariate thresholding method for multiwavelet...