Title :
The double-density dual-tree DWT
Author :
Selesnick, Ivan W.
Author_Institution :
Dept. of Electr. & Comput. Eng., Polytech. Univ., Brooklyn, NY, USA
fDate :
5/1/2004 12:00:00 AM
Abstract :
This paper introduces the double-density dual-tree discrete wavelet transform (DWT), which is a DWT that combines the double-density DWT and the dual-tree DWT, each of which has its own characteristics and advantages. The transform corresponds to a new family of dyadic wavelet tight frames based on two scaling functions and four distinct wavelets. One pair of the four wavelets are designed to be offset from the other pair of wavelets so that the integer translates of one wavelet pair fall midway between the integer translates of the other pair. Simultaneously, one pair of wavelets are designed to be approximate Hilbert transforms of the other pair of wavelets so that two complex (approximately analytic) wavelets can be formed. Therefore, they can be used to implement complex and directional wavelet transforms. The paper develops a design procedure to obtain finite impulse response (FIR) filters that satisfy the numerous constraints imposed. This design procedure employs a fractional-delay allpass filter, spectral factorization, and filterbank completion. The solutions have vanishing moments, compact support, a high degree of smoothness, and are nearly shift-invariant.
Keywords :
FIR filters; Hilbert transforms; approximation theory; discrete wavelet transforms; filtering theory; spectral analysis; trees (mathematics); FIR filter; Hilbert transform approximation; discrete wavelet transform; distinct wavelet; double-density dual-tree DWT; dyadic wavelet tight frames; filterbank completion; finite impulse response filters; fractional-delay allpass filter; scaling function; spectral factorization; Continuous wavelet transforms; Discrete wavelet transforms; Engineering profession; Filter bank; Finite impulse response filter; Image processing; Noise reduction; Signal processing; Wavelet analysis; Wavelet transforms;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2004.826174