Two-Dimensional Filtering Method Using Systems of Local Model Functions for Muonogram Analysis

A two-dimensional filtering method, based on the construction of systems of approximating sliding local model functions with their subsequent weighted averaging, is proposed. A two-dimensional filtering algorithm based on the summation of approximating sliding piecewise-linear model functions with weight coefficients is developed. Optimization of the parameters of the filtering algorithm is considered. The results of testing the filtering algorithm and calculating its optimal parameters on model muonograms are presented. A comparative estimation of the algorithm’s errors is made. An example of testing the developed method of two-dimensional filtering on an experimental muonogram is presented; the results of the muonogram’s analysis are described.