Title :
Adapted waveform “de-noising” for medical signals and images
Author :
Coifman, Ronald R. ; Wickerhauser, Mladen Victor
Author_Institution :
Dept. of Math., Yale Univ., New Haven, CT, USA
Abstract :
Our goal is to describe tools for adapting methods of analysis to various tasks occurring in harmonic and numerical analysis and signal processing. By choosing an orthonormal basis, in which space and frequency are suitably localized, one can achieve both understanding of structure and efficiency in computation. In fact, the search for computational efficiency is intimately related to efficiency in representation (i.e., compression) and to pattern extraction, or structural understanding
Keywords :
Fourier transforms; adaptive codes; data compression; feature extraction; harmonic analysis; image coding; image representation; medical image processing; medical signal processing; signal representation; waveform analysis; wavelet transforms; adapted waveform de-noising; compression; computational efficiency; frequency; harmonic analysis; medical images; medical signals; numerical analysis; orthonormal basis; pattern extraction; representation; signal processing; space; structural understanding; Biomedical imaging; Frequency; Information analysis; Intersymbol interference; Noise reduction; Signal analysis; Signal processing; Signal processing algorithms; Wavelet analysis; Wavelet packets;
Journal_Title :
Engineering in Medicine and Biology Magazine, IEEE
