Multiscale sub-octave wavelet transform for de-noising and enhancement

Laine, Andrew F.; Zong, Xuli

This paper describes an approach for accomplishing sub- octave wavelet analysis and its discrete implementation for noise reduction and feature enhancement. Sub-octave wavelet transforms allow us to more closely characterize features within distinct frequency bands. By dividing each octave into sub-octave components, we demonstrate a superior ability to capture transient activities in a signal or image more reliably. De-noising and enhancement are accomplished through techniques of minimizing noise energy and nonlinear processing of transform coefficient energy by gain.


Also Published In

Wavelet applications in signal and image processing IV : 6-9 August, 1996, Denver, Colorado ; Proceedings of SPIE, vol. 2825

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Academic Units
Biomedical Engineering
Published Here
August 25, 2010