TLS data denoising by range image processing

The work described in this paper deals with denoising of fine detail in terrestrial laser scanner (TLS) data for close‐range applications. In contrast to other denoising methods described in the literature, the method described here puts the problem back into two dimensions. In the proposed method, data from each instrument station is processed by denoising the range image as a 2D function. Then, after denoising, the registration process is applied to obtain the final 3D point cloud. Two image denoising methods are tested. Wavelet analysis and a “non‐local means” (NL‐means) algorithm are applied to archaeological objects of sizes described as medium (around one cubic metre) and small (around one cubic decimetre). The rich relief of these objects proves the efficiency of the method on all kinds of surface shape. The experience shows that the NL‐means method achieves good results: the standard deviation of 2 mm in the raw data is decreased to 1 mm. Besides, NL‐means denoising requires very few parameters to be set (generally two) whilst wavelet denoising requires many. Hence, the extreme simplicity of the NL‐means method makes it much more efficient and suitable for use by non‐specialists. The method, which slightly modifies the standard production process and inherits the algorithmic complexity of the classical 2D image processing schemes, allows the range of applications of TLS to be extended to small and finely detailed objects.