Classification of Airborn Laser Scanner Data by Using Bilateral Minimum/Maximum Filters

Abstract

We propose a new classification feature for airborn laser scanner data by using bilateral minimum/maximum filters for classification. Through experiments which are classified airborn laser scanner data to building, ground, and tree, we verify the effectiveness of the proposed feature. Furthermore, we show that it can perform a highly accurate classification by combining the proposed feature and a conventional feature (Lodha et al., 2006). Finally we comment on the respects in which the proposed feature is improved and on future prospects.