A matched filter data smoothing algorithm

An efficient spatial smoothing algorithm for filtering data while preserving spatial detail is obtained using the system (impulse response) function of the sensor. In contrast to the normal procedure for determining the filter coefficients for an arbitrary system function, this technique does not involve the use of Fourier transforms. The algorithm results in optimal smoothing within the constraints of retaining good vertical detail after only three or four iterations. A refinement of this procedure involving higher-order filter functions produced the equivalent operation in a single pass. The spatial filtering coefficients are obtained analytically for the frequently applicable Gaussian system function. The efficiency of this procedure is illustrated by filtering simulation, logs, and spectral data. For real-time smoothing of nuclear log data, a filter length of five times the vertical resolution is required