Surface roughness analysis often yields varying results for the same sample due to different spatial frequency (wave vector) bandwidths of measuring instruments. This study addresses this variability by employing power spectral density (PSD) calculations, which effectively compensate for the limitations of individual instrument bandwidths. Employing a contact method of surface profilometry, roughness profiles across different wavelength ranges were analyzed, and their correlation with standard surface roughness parameters was explored. The implementation of power spectrum analysis on paper and paperboard surface roughness profiles facilitates the segregation of roughness characteristics over diverse wavelength ranges. Results showed that the predominant contributors to the surface roughness of paper and paperboard, such as fibers, fins, and fillers, predominantly fall within 10–1,000 μm. © 2023 Korean Technical Assoc. of the Pulp and Paper Industry. All rights reserved.
