Spectral graph based approach for analysis of 3D lidar point clouds

Download
2017
Bayram, Eda
Airborne Laser Scanning is a well-known remote sensing technology, which provides quite dense and highly accurate, yet unorganized, point cloud descriptions of the earth surface. However, processing of such a 3D point cloud is quite challenging due to its irregular structure and 3D geometry. In this thesis,two novel approaches for the analysis of unorganized 3D point cloud data are proposed, specifically the ones that are generated by the airborne mounted LIDAR sensor. These methods rely on the spectral graph based and graph signal processing techniques which gain attention in the recent years. The state-of-the-art techniques addressing the problems of LIDAR point clouds are first examined. Next, the theory presented by the spectral graph based methods is reviewed to analyze their solutions. Since irregular discrete data lying on a high dimensional geometry, such as LIDAR point clouds, can be conveniently represented by weighted graphs, spectral graph methods based on such weighted graphs enable spectral analysis of the data representation, as in classical Fourier analysis for signal processing. In the light of the revisited spectral graph literature, one can examine techniques for clustering as well as edge detection problems by using graph representation of the unorganized 3D point clouds. The graph based representation introduces the opportunity of analysis of the signal over its original input space; therefore, it provides qualified comprehension of the data. Based on simulations, it is shown that the graph spectral solutions can acquire remarkable advance in the analysis of unorganized 3D point clouds and the experimental results indicate the potentials of this new approach.  

Suggestions

A Graph Signal Filtering Based Approach for Detection of Different Edge Typeson Airborne LiDAR Data
Bayram, Eda; Vural, Elif; Alatan, Abdullah Aydın (2017-09-12)
Airborne Laser Scanning is a well-known remote sensing technology, which provides a dense and highly accurate, yet unorganized point cloud of earth surface. During the last decade, extracting information from the data generated by airborne LiDAR systems has been addressed by many studies in geo-spatial analysis and urban monitoring applications. However, the processing of LiDAR point clouds is challenging due to their irregular structure and 3D geometry. In this study, we propose a novel framework for the d...
A graph signal filtering-based approach for detection of differentedge types on airborne lidar data,
Bayram, Eda; Vural, Elif; Alatan, Abdullah Aydın (2017-09-14)
Airborne Laser Scanning is a well-known remote sensing technology, which provides a dense and highly accurate, yet unorganized point cloud of earth surface. During the last decade, extracting information from the data generated by airborne LiDAR systems has been addressed by many studies in geo-spatial analysis and urban monitoring applications. However, the processing of LiDAR point clouds is challenging due to their irregular structure and 3D geometry. In this study, we propose a novel framework for the d...
Similarity ratio based algorithms to generate SAR superpixels
Akyılmaz, Emre; Leloğlu, Uğur Murat; Department of Geodetic and Geographical Information Technologies (2017)
Synthetic Aperture Radar (SAR) has the capability of working in all weather conditions during day and night that makes it attractive to be used for automatic target detection and recognition purposes. However, it has the problem of high amount of multiplicative speckle noise. Superpixel segmentation as a preprocessing step is an oversegmentation technique that groups similar neighboring pixels into regularly organized segments with approximately the same size. As boundaries of the objects are important elem...
Parameter estimation for instantaneous spectral imaging
Öktem, Sevinç Figen; Davila, Joseph M (2014-05-04)
Spectral imaging is a fundamental diagnostic technique in physical sciences with widespread application. Conventionally, spectral imaging techniques rely on a scanning process, which renders them unsuitable for dynamic scenes. Here we study the problem of estimating the physical parameters of interest from the measurements of a non-scanning spectral imager based on a parametric model. This inverse problem, which can be viewed as a multi-frame deblurring problem, is formulated as a maximum a posteriori (MAP)...
Tracker-aware adaptive detection: An efficient closed-form solution for the Neyman-Pearson case
Aslan, Murat Samil; Saranlı, Afşar; Baykal, Buyurman (Elsevier BV, 2010-09-01)
A promising line of research for radar systems attempts to optimize the detector thresholds so as to maximize the overall performance of a radar detector-tracker pair. In the present work, we attempt to move in a direction to fulfill this promise by considering a particular dynamic optimization scheme which relies on a non-simulation performance prediction (NSPP) methodology for the probabilistic data association filter (PDAF), namely, the modified Riccati equation (MRE). By using a suitable functional appr...
Citation Formats
E. Bayram, “Spectral graph based approach for analysis of 3D lidar point clouds,” M.S. - Master of Science, Middle East Technical University, 2017.