Edge preserving filtering on 3-D seismic data using complex wavelet transforms
Michael A. Jervis · 2006
Wavelet domain hidden Markov Models (HMM) have been proven to be useful tools in signal processing for image denoising and interpolation. Here the complex wavelet transform is used with a HMM and applied to the problem of noise reduction on post-stack seismic data volumes. HMM aim to capture the statistical structure of smooth (data) and singular (edgy) parts of the signal. Experiments on real seismic data show improved separation of signal and noise after filtering compared with regular wavelet transform filtering methods and principle component filtering.