08-06-2016, 04:47 PM
Introduction
It turns out that, for some applications of the discrete wavelet transform, improvements can be obtained by using an expansive wavelet transform in place of a critically-sampled one. (An expansive transform is one that converts an N-point signal into M coefficients with M > N.) There are several kinds of expansive DWTs; here we describe the dual-tree complex discrete wavelet transform.
It turns out that, for some applications of the discrete wavelet transform, improvements can be obtained by using an expansive wavelet transform in place of a critically-sampled one. (An expansive transform is one that converts an N-point signal into M coefficients with M > N.) There are several kinds of expansive DWTs; here we describe the dual-tree complex discrete wavelet transform.
