International Journal of Advanced Research in Electrical Electronics and Instrumentation Engineering · 2013 · 60 citations · 3 references
EngineeringElectrical EngineeringBiomedical Signal ProcessingDiagnostic ImagingTime Series AnalysisDigital Image ProcessingDigital Signal ProcessingImage ProcessingNoise ReductionSignal Detection TheorySignal ProcessingDenoisingDiscrete Wavelet TransformFilter BanksMulti-resolution AnalysisNon-stationary NoiseSignal DenoisingWavelet DenoisingWavelet Transform
This paper presents a comparative study of different wavelet denoising techniques and the results obtained were examined. The denoising process rejects noise by thresholding in the wavelet domain. It is observed that „rigrsure„ method gives optimum performance. Discrete wavelet transform has the benefit of giving a joint timefrequency representation of the signal. Also it is suitable for both stationary and non stationary signals and is the most appropriate system in the field of signal detection. Discrete wavelet transform is implemented through multi resolution analysis and digital filter banks
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De-noising by soft-thresholding
David L. Donoho · IEEE Transactions on Information Theory · 1995 · 9.6K citations
Ideal spatial adaptation by wavelet shrinkage
David L. Donoho, Iain M. Johnstone · Biometrika · 1994 · 7.8K citations