StudiesOpen Theses
Registrierung von Punktwolken mittels kleinste Quadrate Ausgleichung

Registration of point clouds using Least Squares Adjustment

Team:  Politz, Brenner
Year:  2019

Introduction and goals of this thesis

For their territory, national survey departments have extensive Airborne Laser Scanning (ALS) point clouds with moderate point densities, and a high position and height accuracy. The national survey departments also derive point clouds from aerial flight operations using an algorithm called Dense Image Matching (DIM). These point clouds have a high geometrical and radiometric resolution. For change detection between different points in time as well as for updating the official digital terrain and digital surface models, the correct registration of different point clouds is a crucial part in the processing chain.

The goal of this thesis is to determine global transformation parameter for point cloud tiles or individual flight stripes using the information of local transformation parameters. The local transformation parameters should be derived using least square adjustment considering the different attributes of ALS and DIM point clouds. The quality of those local transformations should be used to weight the observations in a global alignment over a region, which will consequently return stable and uniform global registration parameters and thus will be able to support tiles with weak local transformation results. 


1.    Introduction into the point cloud data and relevant algorithms and literature

2.    Registration of points within a tile using least square adjustment considering point cloud specific characteristics, e.g. different normal vectors or the deviation to a local plane

3.    Evaluation of suitable criteria for the quality of registration parameters

4.    Alignment of the transformation parameters for several individual areas in a joint manner considering those suitable quality criteria. Tile and stripe processing should be examined

5.    Registration of some chosen points or small subareas within a point cloud tile and generation of stabile transformation parameters for the whole region. Tile and stripe processing should be examined.

6.    Other tests and evaluations concerning the minimal and maximal boundaries of observations (tiles/strips) and their influence on the registration parameters and their results

7.    Documentation and presentation of the results


Programming knowledge in Python desirable


Florian Politz (e-mail, phone: 0511 762-19436)

apl. Prof. Dr.-Ing. Claus Brenner (e-mail, phone: 0511 762-5076)


Institut of Cartography and Geoinformatics, Appelstraße 9a, 30167 Hannover, room 616