Information-preserving Surface Restoration and Feature Extraction for Digital Elevation Models
نویسنده
چکیده
Pre-processing such as ltering data in order to remove or at least reduce noise is a crucial step because information which is lost during this ltering cannot be recovered in subsequent steps. It is a well-known fact, that linear ltering 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 to use an algorithm for parameterfree information-preserving surface restoration. As we do not want to evaluate the results of the ltering only qualitatively by visual inspection, we examine the innuence of pre-processing on feature extraction for digital elevation models and discuss quantities for the evaluation of these innuences. 1 INTRODUCTION
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