IEEE Transactions on Signal Processing · 1999 · 129 citations · 21 references
EngineeringBiomedical EngineeringBiomedical ImagingComputer VisionTime Series AnalysisDigital Image ProcessingDigital Signal ProcessingImage FilteringImage ProcessingSignal ProcessingBasis FunctionsDenoisingDiscrete Wavelet TransformFiltersMomentsWavelet AnalysisWavelet DenoisingWavelet Transform
The discrete wavelet transform (DWT) is usually carried out by filterbank iteration; however, for a fixed number of zero moments, this does not yield a discrete-time basis that is optimal with respect to time localization. This paper discusses the implementation and properties of an orthogonal DWT, with two zero moments and with improved time localization. The basis is not based on filterbank iteration; instead, different filters are used for each scale. For coarse scales, the support of the discrete-time basis functions approaches two thirds that of the corresponding functions obtained by filterbank iteration. This basis, which is a special case of a class of bases described by Alpert (1992, 1993), retains the octave-band characteristic and is piecewise linear (but discontinuous). Closed-form expressions for the filters are given, an efficient implementation of the transform is described, and improvement in a denoising example is shown. This basis, being piecewise linear, is reminiscent of the slant transform, to which it is compared.
21
De-noising by soft-thresholding
David L. Donoho · IEEE Transactions on Information Theory · 1995 · 9.6K citations
Orthogonal transforms for digital signal processing
K.R. Rao, N. Ahmed · 2005 · 837 citations
Engineering, Electrical Engineering, Digital Communication +4
Noise reduction using an undecimated discrete wavelet transform
Markus Lang, Jan E. Odegard, C.S. Burrus et al. · IEEE Signal Processing Letters · 1996 · 485 citations