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Terrestrial Laser Scanning (TLS) is a well-known remote sensing tool that enables precise 3D acquisition of surface morphology\udfrom distances of a few meters to a few kilometres. The morphological representations obtained are important in engineering\udgeology and rock mechanics, where surface morphology details are of particular interest in rock stability problems and engineering\udconstruction. The actual size of the discernible surface detail depends on the instrument range error (noise effect) and effective data\udresolution (smoothing effect). Range error can be (partly) removed by applying a denoising method. Based on the positive results\udfrom previous studies, two denoising methods, namely 2D wavelet transform (WT) and non-local mean (NLM), are tested here, with\udthe goal of obtaining roughness estimations that are suitable in the context of rock engineering practice. Both methods are applied in\udtwo variants: conventional Discrete WT (DWT) and Stationary WT (SWT), classic NLM (NLM) and probabilistic NLM (PNLM).\udThe noise effect and denoising performance are studied in relation to the TLS effective data resolution. Analyses are performed on\udthe reference data acquired by a highly precise Advanced TOpometric Sensor (ATOS) on a 20x30 cm rock joint sample. Roughness\udratio is computed by comparing the noisy and denoised surfaces to the original ATOS surface. The roughness ratio indicates the\udsuccess of all denoising methods. Besides, it shows that SWT oversmoothes the surface and the performance of the DWT, NLM and\udPNLM vary with the noise level and data resolution. The noise effect becomes less prominent when data resolution decreases

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

EVALUATION OF WAVELET AND NON-LOCAL MEAN DENOISING OF TERRESTRIAL LASER SCANNING DATA FOR SMALL-SCALE JOINT ROUGHNESS ESTIMATION