Information-preserving surface restoration and feature extraction for digital elevation models

Preprocessing such as filtering data in order to remove or at least reduce noise is a crucial step because information which is lost during this filtering cannot be recovered in subsequent steps. It is a well-known fact, that linear filtering does not only reduce noise, but may also lead to a loss of information due to the global smoothing, regardless of structures in the data. In order to overcome these drawbacks, we propose using an algorithm for parameter free information- preserving surface restoration. As we do not want to evaluate the results of the filtering only qualitatively by visual inspection, we examine the influence of pre-processing on feature extraction for digital elevation models and discuss quantities for the evaluation of these influences.