A Framework for the Registration and Segmentation of Heterogeneous Lidar Data

作者：Al Durgham M^*; Habib A

来源：Photogrammetric Engineering and Remote Sensing, 2013, 79(2): 135-145.

DOI：10.14358/PERS.79.2.135

Lidar has been established over the past few years as a mainstream tool for the acquisition of three dimensional point data. Besides the conventional mapping missions, lidar has proven to be very useful for a wide spectrum of applications such as forestry, urban planning, structural deformation analysis, and reverse engineering. In the context of a nationwide dataset, it is safe to assume that multiple laser scanners are under different conditions to collect the data. Current registration and segmentation algorithms assume homogeneity in the local point density and accuracy which is an invalid assumption that cannot be tolerated. As a consequence of the wide range of lidar sensors currently available, it is becoming crucial to develop algorithms for the registration and segmentation of lidar data with significantly varying characteristics (i.e., varying point density and accuracy). In this paper, a methodology for the optimal registration and segmentation of heterogeneous lidar data is presented. An example of integrating airborne and terrestrial laser scans is presented and followed by a discussion of the pros of the integration process.

• 出版日期2013-2