Fast algorithm of the robust Gaussian regression filter for areal surface analysis – W Zeng, X Jiang, and P J Scott

Abstract
In this paper, the general model of the Gaussian regression filter for areal surface analysis is
explored. The intrinsic relationships between the linear Gaussian filter and the robust filter are
addressed. A general mathematical solution for this model is presented. Based on this
technique, a fast algorithm is created. Both simulated and practical engineering data
(stochastic and structured) have been used in the testing of the fast algorithm. Results show
that with the same accuracy, the processing time of the second-order nonlinear regression
filters for a dataset of 1024∗1024 points has been reduced to several seconds from the several
hours of traditional algorithms.