Abstract

A new implementation of the Discrete Wavelet Transform is presented for applications such as image restoration and enhancement. It employs a dual tree of wavelet filters to obtain the real and imaginary parts of the complex wavelet coefficients. This introduces limited redundancy (4 : 1 for 2-dimensional signals) and allows the transform to provide approximate shift invariance and directionally selective filters (properties lacking in the traditional wavelet transform) while preserving the usual properties of perfect reconstruction and computational efficiency. We show how the dual-tree complex wavelet transform can provide a good basis for multiresolution image denoising and de-blurring. 1 INTRODUCTION Although the Discrete Wavelet Transform (DWT) in its maximally decimated form (Mallat's dyadic filter tree [1]) has established an impressive reputation as a tool for image compression, its use for other signal analysis and reconstruction tasks, such as image restoration and enhancem...

Citations

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1	A Magarey and N G Kingsbury, "An improved motion estimation algorithm using complex wavelets - F - 1996