Complex linear-phase biorthogonal filterbanks with approximately analytic wavelets

In this paper, approximately analytic wavelets associated with a single filterbank tree are designed. It is shown that if the scaling filters are made analytic, the wavelets also become analytic. In other words, the real and imaginary parts of the scaling filters form a Hilbert transform pair. They have identical magnitude and phase shifts of @p/2 and [email protected]/2 for the frequency range (0,@p) and ([email protected], 0), respectively. Conjugate symmetric filters are used in the biorthogonal setting so that the phase relationship is structurally guaranteed. The error between the magnitudes of real and imaginary parts of the scaling filters is then minimized subject to biorthogonality. As a result complex, linear-phase wavelet bases is obtained which have vanishing moments. The error level in the negative/positive frequency suppression for a length 10 filterbank with 5 vanishing moments is of the order 10^-^3. The designed wavelets may be potentially useful in applications such as face recognition, image segmentation and texture analysis.

[1]  Marimuthu Palaniswami,et al.  Design of approximate Hilbert transform pair of wavelets with exact symmetry [filter bank design] , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[2]  Ivan W. Selesnick,et al.  The design of approximate Hilbert transform pairs of wavelet bases , 2002, IEEE Trans. Signal Process..

[3]  Richard Baraniuk,et al.  Phase and magnitude perceptual sensitivities in nonredundant complex wavelet representations , 2003, The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003.

[4]  Ingrid Daubechies,et al.  Ten Lectures on Wavelets , 1992 .

[5]  J. Lina,et al.  Complex Daubechies Wavelets , 1995 .

[6]  Truong Q. Nguyen,et al.  A study of two-channel complex-valued filterbanks and wavelets with orthogonality and symmetry properties , 2002, IEEE Trans. Signal Process..

[7]  Nick G. Kingsbury,et al.  Design of Q-shift complex wavelets for image processing using frequency domain energy minimization , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[8]  Benjamin Belzer,et al.  Complex, linear-phase filters for efficient image coding , 1995, IEEE Trans. Signal Process..

[9]  P. Abry,et al.  Multiresolution transient detection , 1994, Proceedings of IEEE-SP International Symposium on Time- Frequency and Time-Scale Analysis.

[10]  LinLin Shen,et al.  A review on Gabor wavelets for face recognition , 2006, Pattern Analysis and Applications.

[11]  Julian Magarey,et al.  Motion estimation using a complex-valued wavelet transform , 1998, IEEE Trans. Signal Process..

[12]  Harri Ojanen,et al.  Orthonormal Compactly Supported Wavelets with Optimal Sobolev Regularity , 1998, math/9807089.

[13]  N. Kingsbury Complex Wavelets for Shift Invariant Analysis and Filtering of Signals , 2001 .

[14]  Xiao-Ping Zhang,et al.  Orthogonal complex filter banks and wavelets: some properties and design , 1999, IEEE Trans. Signal Process..

[15]  Richard Baraniuk,et al.  The Dual-tree Complex Wavelet Transform , 2007 .

[16]  Hüseyin Özkaramanli,et al.  Hilbert transform pairs of biorthogonal wavelet bases , 2006, IEEE Transactions on Signal Processing.