Recovering trivariate functions by data on tracks

In this paper we present a technique for recovering functions of three variables when scattered data on tracks are given. The aim is to obtain a good quality of reproduction with a contained computational cost. In order to do this we exploit the data structure which allows to solve lower dimension problems