@Article{, title={Design and Implementation of New Computation Method for Multiwavelets Decomposition as 1't and 2nd Approximations}, author={Adel A. Al Wahaab and Amaal Kadim Dawood and Enas Mohammad Hussein}, journal={Journal of College of Education مجلة كلية التربية}, volume={}, number={3}, pages={152-185}, year={2009}, abstract={One of the important differences between multiwaveletsand scalar wavelets is that each channel in the filter bank has avector-valued output as scalar-valued input signal mustsomehow be converted into a suitable vector-valued signal .Thisconversion is called preprocessing[1]. Preprocessing is mappingprocess which is done by a prefilter. A postfilter just does theopposite. The most obvious way to get two input rows from agiven signal to repeat the signal [2]. Two rows go to into thernultifilter bank. This procedure is called "Repeated row" whichintroduce over sampling of data by a factor of 212]. Two rowsgo into the multifilter bank. For data compression , where one istrying to find compact transform representation for a dataset[3],it is imperative to find critically sampled multiwavelet transformschemes which this paper focus on finding a simple and easy tofollow algorithm for its computation. One famous multiwaveletfilter used here is the GHM filter proposed by Geronimo. TheGHM basis offers a combination of orthogonally, symmetry,and compact support, which can not be achieved by any scalarwavelet basis [4]. Using a computer program for the proposedmethod, an example test on tiger image is verified which showsimage properties after a single level decomposition and thereconstructed image after reconstruction'

} }