Coherent noise removal in seismic data with redundant multiscale directional filters

Directional filters are commonly used tools in modern seismic data processing to address coherent signals, depending on their apparent slowness or slope. This operation enhances the characterization of the great variety of signals present in a seismic dataset that enables a better characterization of the subsurface structure. This paper compares two complementary local adaptive multiscale directional filters: a directional filter bank based on dual-tree M-band wavelets and a novel local slant stack transform (LSST) based filter in the timescale domain. Their differences reside in redundancy levels and slope (directional) resolution. A structural similarity index measure has been employed to objectively compare both approaches on a real seismic dataset example.