A 3-D range sensor using triangulation collects large files of range data for an object surface. The available range data may be reduced to a more manageable set for surface reconstruction by using multiresolution analysis and wavelet transformation. This reduction of the data file size may be achieved without losing the essential characteristics of the surface by imposing proper requirements on the scaling function of the wavelet transform. These requirements are determined by considering either the type of scanned surface or the reconstruction method used here: a polyhedral surface fitting. Wavelet transformations corresponding to different scaling functions are used to produce reduced data sets from the original one; subsampling is achieved using the Battle-Lemarié linear spline and cubic spline scaling functions and an eight-coefficient Daubechies compactly supported scaling function. A short description of the acquired range data, the application of wavelet transformation to the data, and test results on surface reconstruction are presented.