Shift invariant properties of the dual-tree complex wavelet transform

Authors:
N. Kingsbury
Affiliations:
Dept. of Eng., Cambridge Univ., UK
Venue:
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03
Year:
1999

Citing 0
Cited 15

Image denoising with complex ridgelets

Pattern Recognition
A basis for efficient representation of the S-transform

Digital Signal Processing
Pattern recognition with SVM and dual-tree complex wavelets

Image and Vision Computing
DT-CWT Feature Combined with ONPP for Face Recognition

Computational Intelligence and Security
Image Denoising Using Three Scales of Wavelet Coefficients

ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II
Complex wavelet transform-based face recognition

EURASIP Journal on Advances in Signal Processing
Invariant pattern recognition using radon, dual-tree complex wavelet and Fourier transforms

Pattern Recognition
Auto-correlation wavelet support vector machine

Image and Vision Computing
Construction of Hilbert transform pairs of wavelet bases and Gabor-like transforms

IEEE Transactions on Signal Processing
Anomaly detection through packet header data

ICICS'09 Proceedings of the 7th international conference on Information, communications and signal processing
Implementation and application of local computation of wavelet coefficients in the dual-tree complex wavelets

ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Higher density wavelet frames with symmetric low-pass and band-pass filters

Signal Processing
Improvement in image denoising technique based on dual - tree wavelet transform and multiresolution local contrast entropy

Machine Graphics & Vision International Journal
Geometric invariant domain for image watermarking

IWDW'06 Proceedings of the 5th international conference on Digital Watermarking
Pulmonary crackle detection using time-frequency and time-scale analysis

Digital Signal Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

We discuss the shift invariant properties of a new implementation of the discrete wavelet transform, which employs a dual-tree of wavelet filters to obtain the real and imaginary parts of complex wavelet coefficients. This introduces limited redundancy (2/sup m/:1 for m-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 with good well-balanced frequency responses.