Fast Algorithm of the Robust Gaussian Regression Filter for Areal Surface Analysis

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20 Citations (Scopus)

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.

Original languageEnglish
Article number055108
JournalMeasurement Science and Technology
Volume21
Issue number5
DOIs
Publication statusPublished - 31 Mar 2010

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Surface analysis
Fast Algorithm
regression analysis
Regression
Filter
filters
Gaussian Filter
Linear Filter
Nonlinear Regression
Engineering
Testing
engineering
Processing
Model

Cite this

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AB - 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.

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KW - Surface Characterization

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