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B-spline signal processing. I. Theory

IEEE Transactions on Signal Processing · 1993 · Vol. 41(2) · pp. 821–833
Michaël UnserAkram AldroubiM. Eden

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.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Image and Signal Denoising MethodsAdvanced Numerical Analysis TechniquesAdvanced Computational Techniques in Science and EngineeringSmoothingSpline (mechanical)MathematicsAlgorithmSignal processingSmoothing splineB-splineThin plate splineNoise reductionLinear filter
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References
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IEEE Transactions on Medical Imaging · 1983 · 815 citations
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