Abstract
Abstract. The precision of Terrestrial Laser Scanning (TLS) data depends mainly on the inherent random range error, which hinders extraction of small details from TLS measurements. New post processing algorithms have been developed that reduce or eliminate the noise and therefore enable modelling details at a smaller scale than one would traditionally expect. The aim of this research is to find the optimum denoising method such that the corrected TLS data provides a reliable estimation of small-scale rock joint roughness. Two wavelet-based denoising methods are considered, namely Discrete Wavelet Transform (DWT) and Stationary Wavelet Transform (SWT), in combination with different thresholding procedures. The question is, which technique provides a more accurate roughness estimates considering (i) wavelet transform (SWT or DWT), (ii) thresholding method (fixed-form or penalised low) and (iii) thresholding mode (soft or hard). The performance of denoising methods is tested by two analyses, namely method noise and method sensitivity to noise. The reference data are precise Advanced TOpometric Sensor (ATOS) measurements obtained on 20 × 30 cm rock joint sample, which are for the second analysis corrupted by different levels of noise. With such a controlled noise level experiments it is possible to evaluate the methods’ performance for different amounts of noise, which might be present in TLS data. Qualitative visual checks of denoised surfaces and quantitative parameters such as grid height and roughness are considered in a comparative analysis of denoising methods. Results indicate that the preferred method for realistic roughness estimation is DWT with penalised low hard thresholding.
Highlights
In the last few decades Terrestrial Laser Scanning (TLS) is increasingly used in the field of engineering geology for a growing array of applications (Fowler, 2011; Fernández-Steeger et al, 2009)
Because of remote and fast acquisition that results in relative high resolution and accuracy data, TLS is valuable for in-situ rock mass characterization (Tonon and Kottenstette, 2006); especially for estimating geometrical parameters (Slob, 2010)
Experiments were executed on Advanced TOpometric Sensor (ATOS) measurements which have much higher precision than any TLS data
Summary
In the last few decades Terrestrial Laser Scanning (TLS) is increasingly used in the field of engineering geology for a growing array of applications (Fowler, 2011; Fernández-Steeger et al, 2009). Because of remote and fast acquisition that results in relative high resolution and accuracy data, TLS is valuable for in-situ rock mass characterization (Tonon and Kottenstette, 2006); especially for estimating geometrical parameters (Slob, 2010). Roughness direction should be consistent with expected rock mass movements (shear direction). Waviness can be described as a large-amplitude and low-frequency signal. It has been defined by (Priest, 1993) as “surface irregularities with a wavelength greater than about 10 cm”. Unevenness can be described as a small-amplitude and high-frequency signal. It covers finer scales of 5 to 10 cm and is superimposed on the waviness
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