Abstract
Engineering surfaces are comprised of a range of spatial wavelengths. Filtering techniques are commonly adopted to separate the different wavelength components into well-defined bandwidths. Filtering is done prior to numerical characterization and it is also essential for extracting information needed to provide process feedback and establish functional correlation. This paper reviews commonly used filters in surface metrology like the 2RC, Gaussian and several new ones currently under research such as the spline, morphological, wavelets, regression filters and robust regression filters. The need for these new filters and examples illustrating the features of these filters are also presented.
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