KEYWORDS: Image segmentation, LIDAR, Image processing algorithms and systems, 3D modeling, Buildings, Dysprosium, Vegetation, 3D visualizations, 3D scanning, Image processing
Airborne LiDAR data are useful for 3D terrain visualization. Segmentation of the data set is especially important for
extracting vector data in scenes containing man-made structures. In a graph theoretic formulation, each pixel is a node in
a connected graph. The likelihood of an edge existing between two pixels is encoded as the weight between the nodes.
Segmentation becomes a graph partitioning that minimizes the weights of the cut links. We combine texture analysis,
morphological operators, and the normalized-cut graph-theoretic algorithm to segment lidar data sets. Experimental
results using collected data demonstrate the efficacy of our method.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.