The development of efficient strategies to document cultural heritage sites is an active research field. One promising avenue to address that need may be found in the use of portable laser scanners. Such scans provide a mapping-grade level of accuracy, yet their level of characterization is limited by the low resolution of the generated point cloud and by the relatively noisy measurements. In this paper we study methods to attenuate the noisy responses as a means to improve the data quality and highlight the underlying structure. Unlike the prevailing plane-fitting-based filtering approaches that tend to blur salient features, we consider the use of local structure properties in our denoising strategy. We use the normal-based bilateral filtering of point clouds as a platform, yet introduce new normal preservation concepts whose incorporation significantly improves the overall denoising process performance. Results demonstrate how our proposed solution outperforms the standard plane-filtering and the naive bilateral approach. The attenuation we achieve yields a more visually pleasing entity description as well as simplified processing of subsequent procedures, including feature extraction and semantic segmentation.