The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
B-spline signal processing. I. Theory
Abstract
The use of continuous B-spline representations for signal processing applications such as interpolation, differentiation, filtering, noise reduction, and data compressions is considered. The B-spline coefficients are obtained through a linear transformation, which unlike other commonly used transforms is space invariant and can be implemented efficiently by linear filtering. The same property also applies for the indirect B-spline transform as well as for the evaluation of approximating representations using smoothing or least squares splines. The filters associated with these operations are fully characterized by explicitly evaluating their transfer functions for B-splines of any order. Applications to differentiation, filtering, smoothing, and least-squares approximation are examined. The extension of such operators for higher-dimensional signals such as digital images is considered.>
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Cites
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Cited by
Ashburner, J., & Friston, K. J. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.02.018 · Cited by 7,507
A Review of Geometric Transformations for Nonrigid Body Registration
Holden, M. (2008) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2007.904691 · Cited by 369
Fractional Delay Filters—Design and Applications
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Metadata
- Authors
- Unser, M., Aldroubi, A., & Eden, M.
- Venue
- IEEE Transactions on Signal Processing
- Published
- 1993
- Volume
- 41
- Issue
- 2
- Pages
- 821-833
- ISSN
- 1053-587X (ISSN-L)
- OpenAlex
- W2050921210
- Cited by
- 940
- References
- 24
- FWCI
- 7.77
- Type
- journal article
- Language
- en
- Open access
- closed
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