Extracting buildings from and regularizing boundaries in airborne lidar data using connected operators

ABSTRACT The location of building boundary is a crucial prerequisite for geographical condition monitoring, urban management, and building reconstruction. This paper presents a framework that employs a series of algorithms to automatically extract building footprints from airborne (light detection and ranging (lidar)) data and image. Connected operators are utilized to extract building regions from lidar data, which would not produce new contours nor change their position and have very good contour-preservation properties. First, the building candidate regions are separated from lidar-derived digital surface model (DSM) based on a new method proposed within this paper using connected operators, and trees are removed based on the normalized difference vegetation index (NDVI) value of image. Then, building boundaries are identified and building boundary lines are traced by ‘sleeve’ line simplification method. Finally, the principal directions of buildings are used to regularize the directions of building boundary lines. International Society for Photogrammetry and Remote Sensing (ISPRS) data sets in Vaihingen whose point spacing is about 0.4 m from urbanized areas were employed to test the proposed framework, and three test areas were selected. A quantitative analysis showed that the method proposed within this paper was effective and the average offset values of simple and complex building boundaries were 0.2–0.4 m and 0.3–0.6 m, respectively.

[1]  Eunju Kwak,et al.  Automatic representation and reconstruction of DBM from LiDAR data using Recursive Minimum Bounding Rectangle , 2014 .

[2]  A. Saalfeld,et al.  LINEAR-TIME SLEEVE-FITTING POLYLINE SIMPLIFICATION ALGORITHMS , 2008 .

[3]  Henk J. A. M. Heijmans.  Connected Morphological Operators for Binary Images , 1999, Comput. Vis. Image Underst..

[4]  Liqiang Zhang,et al.  Urban building roof segmentation from airborne lidar point clouds , 2012 .

[5]  Jie Shan,et al.  Building Extraction from LiDAR Point Clouds Based on Clustering Techniques , 2008 .

[6]  Christophe Collet,et al.  Connected Component Trees for Multivariate Image Processing and Applications in Astronomy , 2010, 2010 20th International Conference on Pattern Recognition.

[7]  Michael H. F. Wilkinson.  Attribute-space connectivity and connected filters , 2007, Image Vis. Comput..

[8]  C. Briese,et al.  A NEW METHOD FOR BUILDING EXTRACTION IN URBAN AREAS FROM HIGH-RESOLUTION LIDAR DATA , 2002 .

[9]  Philippe Salembier,et al.  Flat zones filtering, connected operators, and filters by reconstruction , 1995, IEEE Trans. Image Process..

[10]  Emmanuel Bertin,et al.  Effective Component Tree Computation with Application to Pattern Recognition in Astronomical Imaging , 2007, 2007 IEEE International Conference on Image Processing.

[11]  Hugues Talbot,et al.  Filtering and segmentation of 3D angiographic data: Advances based on mathematical morphology , 2013, Medical Image Anal..

[12]  Ronald Jones,et al.  Connected Filtering and Segmentation Using Component Trees , 1999, Comput. Vis. Image Underst..

[13]  Domen Mongus,et al.  Computationally Efficient Method for the Generation of a Digital Terrain Model From Airborne LiDAR Data Using Connected Operators , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[14]  I. Dowman,et al.  Data fusion of high-resolution satellite imagery and LiDAR data for automatic building extraction * , 2007 .

[15]  Petros Maragos,et al.  Threshold Superposition in Morphological Image Analysis Systems , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Jean Paul Frédéric Serra.  Connectivity on Complete Lattices , 2004, Journal of Mathematical Imaging and Vision.

[17]  Salman Ahmadi,et al.  An improved snake model for automatic extraction of buildings from urban aerial images and LiDAR data , 2010, Comput. Environ. Urban Syst..

[18]  Domen Mongus,et al.  Ground and building extraction from LiDAR data based on differential morphological profiles and locally fitted surfaces , 2014 .

[19]  Le Wang,et al.  Isprs Journal of Photogrammetry and Remote Sensing a Multi-directional Ground Filtering Algorithm for Airborne Lidar , 2022 .

[20]  Yanming Chen,et al.  Multiscale Grid Method for Detection and Reconstruction of Building Roofs from Airborne LiDAR Data , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[21]  Ronald Jones,et al.  Attribute Openings, Thinnings, and Granulometries , 1996, Comput. Vis. Image Underst..

[22]  Ayman Habib,et al.  INTERPOLATION OF LIDAR DATA AND AUTOMATIC BUILDING EXTRACTION , 2002 .

[23]  Bisheng Yang,et al.  Automated Extraction of Building Outlines From Airborne Laser Scanning Point Clouds , 2013, IEEE Geoscience and Remote Sensing Letters.

[24]  Zhang Shunfu,et al.  A Point Clouds Filtering Algorithm Based on Grid Partition and Moving Least Squares , 2012 .

[25]  Jaewook Jung,et al.  Results of the ISPRS benchmark on urban object detection and 3D building reconstruction , 2014 .

[26]  Yongjun Zhang,et al.  Direct georeferencing of airborne LiDAR data in national coordinates , 2013 .

[27]  P. Axelsson.  DEM Generation from Laser Scanner Data Using Adaptive TIN Models , 2000 .

[28]  Yong Li,et al.  A gradient-constrained morphological filtering algorithm for airborne LiDAR , 2013 .

[29]  C. Brenner,et al.  A generative statistical approach to automatic 3D building roof reconstruction from laser scanning data , 2013 .

[30]  Jon Atli Benediktsson,et al.  Extended Self-Dual Attribute Profiles for the Classification of Hyperspectral Images , 2015, IEEE Geoscience and Remote Sensing Letters.

[31]  M.H.F. Wilkinson,et al.  Connected operators , 2009, IEEE Signal Processing Magazine.

[32]  Aloysius Wehr,et al.  Airborne laser scanning—an introduction and overview , 1999 .

[33]  Jean Cousty,et al.  VOIDD: automatic vessel of intervention dynamic detection in PCI procedures , 2017, ArXiv.

[34]  Keith C. Clarke,et al.  An improved simple morphological filter for the terrain classification of airborne LIDAR data , 2013 .

[35]  J. Shan,et al.  Building boundary tracing and regularization from airborne lidar point clouds , 2007 .

[36]  Chengcui Zhang,et al.  A progressive morphological filter for removing nonground measurements from airborne LIDAR data , 2003, IEEE Trans. Geosci. Remote. Sens..

[37]  J. Niemeyer,et al.  Contextual classification of lidar data and building object detection in urban areas , 2014 .

[38]  Nicolas Passat,et al.  Extraction of complex patterns from multiresolution remote sensing images: A hierarchical top-down methodology , 2012, Pattern Recognit..

[39]  Lin Zhu,et al.  A refined marker controlled watershed for building extraction from DSM and imagery , 2010 .

[40]  George Vosselman,et al.  Experimental comparison of filter algorithms for bare-Earth extraction from airborne laser scanning point clouds , 2004 .

[41]  Le Wang,et al.  MORPHOLOGY-BASED BUILDING DETECTION FROM AIRBORNE LIDAR DATA , 2009 .

[42]  Michel Couprie,et al.  Building the Component Tree in Quasi-Linear Time , 2006, IEEE Transactions on Image Processing.

[43]  Masashi Matsuoka,et al.  Multi-scale solution for building extraction from LiDAR and image data , 2009, Int. J. Appl. Earth Obs. Geoinformation.

[44]  K. Kraus,et al.  Determination of terrain models in wooded areas with airborne laser scanner data , 1998 .

[45]  Emmanuel P. Baltsavias,et al.  A comparison between photogrammetry and laser scanning , 1999 .

[46]  N. Pfeifer,et al.  Neighborhood systems for airborne laser data , 2005 .

[47]  P. Gong,et al.  Filtering airborne laser scanning data with morphological methods , 2007 .

[48]  Ulisses Braga-Neto,et al.  Connectivity on Complete Lattices: New Results , 2002, Comput. Vis. Image Underst..

[49]  B. Žalik,et al.  DETECTION OF PLANAR POINTS FOR BUILDING EXTRACTION FROM LIDAR DATA BASED ON DIFFERENTIAL MORPHOLOGICAL AND ATTRIBUTE PROFILES , 2013 .

[50]  Domen Mongus,et al.  Parameter-free ground filtering of LiDAR data for automatic DTM generation , 2012 .

[51]  Kyoung Mu Lee,et al.  Fusion of Lidar and Imagery for Reliable Building Extraction , 2008 .

[52]  Klaus Tempfli,et al.  AUTOMATIC BUILDING EXTRACTION FROM AIRBORNE LASER SCANNING DATA , 2000 .

[53]  Liang-Chien Chen,et al.  Automated Searching of Ground Points from Airborne Lidar Data Using a Climbing and Sliding Method , 2008 .

[54]  G. Vosselman.  SLOPE BASED FILTERING OF LASER ALTIMETRY DATA , 2000 .

[55]  Ruijin Ma,et al.  Building model reconstruction from LIDAR data and aerial photographs , 2005 .

[56]  Luc Vincent,et al.  Morphological grayscale reconstruction in image analysis: applications and efficient algorithms , 1993, IEEE Trans. Image Process..

[57]  Laurent Wendling,et al.  A document binarization method based on connected operators , 2010, Pattern Recognit. Lett..

[58]  Franz Rottensteiner,et al.  AUTOMATIC EXTRACTION OF BUILDINGS FROM LIDAR DATA AND AERIAL IMAGES , 2002 .

[59]  Norbert Pfeifer,et al.  A Comparison of Evaluation Techniques for Building Extraction From Airborne Laser Scanning , 2009, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[60]  Philippe Salembier,et al.  Antiextensive connected operators for image and sequence processing , 1998, IEEE Trans. Image Process..

[61]  Shu-Ching Chen,et al.  Automatic Construction of Building Footprints From Airborne LIDAR Data , 2006, IEEE Transactions on Geoscience and Remote Sensing.