Multiscale suboctave wavelet transform for denoising and enhancement
Andrew F. Laine, Xuli Zong · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1996
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.