The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
The dual-tree complex wavelet transform
Abstract
The paper discusses the theory behind the dual-tree transform, shows how complex wavelets with good properties can be designed, and illustrates a range of applications in signal and image processing. The authors use the complex number symbol C in CWT to avoid confusion with the often-used acronym CWT for the (different) continuous wavelet transform. The four fundamentals, intertwined shortcomings of wavelet transform and some solutions are also discussed. Several methods for filter design are described for dual-tree CWT that demonstrates with relatively short filters, an effective invertible approximately analytic wavelet transform can indeed be implemented using the dual-tree approach.
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Citations
Cites
Daubechies, I. (1992) · doi:10.1137/1.9781611970104 · Cited by 15,979
The wavelet transform, time-frequency localization and signal analysis
Daubechies, I. (1990) · IEEE Transactions on Information Theory · doi:10.1109/18.57199 · Cited by 6,483
Sparse coding with an overcomplete basis set: A strategy employed by V1?
Olshausen, B. A., & Field, D. J. (1997) · Vision Research · doi:10.1016/s0042-6989(97)00169-7 · Cited by 3,642
Splitting the unit delay [FIR/all pass filters design]
Laakso, T. I., Valimaki, V., Karjalainen, M., & Laine, U. K. (1996) · IEEE Signal Processing Magazine · doi:10.1109/79.482137 · Cited by 1,168
Cited by
Double Sparsity: Learning Sparse Dictionaries for Sparse Signal Approximation
Rubinstein, R., Zibulevsky, M., & Elad, M. (2010) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2009.2036477 · Cited by 616
Wavelet transform based on inner product in fault diagnosis of rotating machinery: A review
Chen, J., Li, Z., Pan, J., Chen, G., Zi, Y., Yuan, J., Chen, B., & He, Z. (2016) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2015.08.023 · Cited by 517
Comprehensive survey of image steganography: Techniques, Evaluations, and trends in future research
Kadhim, I. J., Premaratne, P., Vial, P. J., & Halloran, B. (2019) · Neurocomputing · doi:10.1016/j.neucom.2018.06.075 · Cited by 452
Local diversity and fine-scale organization of receptive fields in mouse visual cortex
Bonin, V., Histed, M. H., Yurgenson, S., & Reid, R. C. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.2974-11.2011 · Cited by 247
Cao, X.-C., Chen, B.-Q., Yao, B., & He, W.-P. (2019) · Computers in Industry · doi:10.1016/j.compind.2018.12.018 · Cited by 208
Metadata
- Authors
- Selesnick, I. W., Baraniuk, R. G., & Kingsbury, N. C.
- Venue
- IEEE Signal Processing Magazine
- Published
- 2005-11
- Volume
- 22
- Issue
- 6
- Pages
- 123-151
- ISSN
- 1053-5888 (ISSN-L)
- OpenAlex
- W2018332268
- Cited by
- 2,475
- References
- 4
- FWCI
- 107.99
- Type
- journal article
- Language
- en
- Open access
- closed
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- Selesnick, I. W., Baraniuk, R. G., & Kingsbury, N. C. (2005). The dual-tree complex wavelet transform. IEEE Signal Processing Magazine. https://doi.org/10.1109/msp.2005.1550194
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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