AN EMPIRICAL-METHOD FOR OPTIMAL ROBUST REGIONAL-RESIDUAL SEPARATION OF GEOPHYSICAL-DATA

Prior to interpretation and further analysis, many datasets must first be separated into regional and residual components. Traditional techn iques are either subjective (e.g., graphical methods) or nonrobust (e. g., all least-squares based methods). Bathymetric data, with their bro ad spectrum, pose serious difficulties to these traditional methods, i n particular those based on spectral decomposition. Spatial median fil ters offer a solution that is robust, objective, and often defines reg ional components similar to those produced graphically by hand. Charac teristics of spatial median filters in general are discussed and a new empirical method is presented for determining the width of the robust median filter that accomplishes an optimal separation of a gridded da taset into its regional and residual components. The method involves t racing the zero-contour of the residual component and evaluating the r atio between the volume enclosed by the surface inside this contour an d the contour's area. The filter width giving the highest ratio (or me an amplitude) is called the Optimal Robust Separator (ORS) and is sele cted as the optimal filter producing the best separation. The techniqu e allows a unique and objective determination of the regional field an d enables researchers to undertake reproducible separations of regiona l and residual components. The ORS method is applied to both synthetic data and bathymetry/topography of the Hawaiian Islands; ways to impro ve the technique wing alternative diagnostic quantities are discussed.