Dense Terrain Extraction from Stereo Imagery Using Semi-Global Matching Frank Obusek Application Engineer LaRSGIS April 24, 2013
HxGN Live June 3-6, 2013 2
ERDAS IMAGINE Spatial Modeler Workshop 4/25 Thursday 1pm 4pm National Wetlands Research Center Conference Room Andy Zusmanis - 27 years with ERDAS/Intergraph 3
ERDAS IMAGINE 2013 Spatial Modeler 4
Dense Terrain Extraction from Stereo Imagery Using Semi-Global Matching Frank Obusek Application Engineer LaRSGIS April 24, 2013
Dense Terrain Extraction from Stereo Imagery 6
Dense Terrain Extraction from Stereo Imagery 7
Dense Terrain Extraction from Stereo Imagery
Point Cloud is the Third Type of Data (Elevation) Vector Point Measurements and Contours have been used historically to represent terrain surfaces. These are combined with break lines to create Triangulated Irregular Networks (TINs) from which surface points can be interpolated. The data representation is a sparse set of highly irregularly space {X,Y,Z} values. Raster They have been converted to gridded formats using various techniques to produce Raster datasets. Delivered as Digital Elevation Models (DEMs). The representation is a dense set of regularly spaced {Z} values. Point Cloud LiDAR data is a collection of points with attributes. The representation is a dense set of semi-regularly spaced {X,Y,Z, Attribute..} values. 9
Point Cloud Benefits LiDAR Point Clouds Attach attributes to each point Multiple returns Accurate Z Flown at night Vegetation penetration 10
Point Cloud Benefits Dense Point Clouds from Stereo Imagery Attach attributes to each point High Point Density Better XY positioning Less expensive than flying LiDAR data Historic point cloud data (pre-lidar times) 11
Heiko Hirschmüller, Ph.D. German Aerospace Center Institute of Robotics and Mechatronics Department of Perception and Cognition Semi-Global Matching (SGM) SGM is a stereo matching method that is based on pixel-wise matching, supported by a global smoothness function that is optimized along multiple paths (Hirschmüller, 2008, 2006 and 2005). It has a regular algorithmic structure and uses simple operations and is therefore well suited for parallel implementation on the CPU using vector commands as well as on the GPU (Ernst and Hirschmüller, 2008) and FPGA (Hirschmüller, 2011). Census is used as matching cost for radiometric robustness (Hirschmüller and Scharstein 2009). The method is quite insensitive to the choice of parameters, which means that it usually does not require parameter tuning. 12
Semi-Global Matching for Geospatial Semi-global matching avoids correlation problems caused by recording or illumination differences or reflections. Facilitates matching at the boundaries of objects or fine structures. You can use these dense point clouds to create precise surface models for highly accurate orthorectification. Source for manual or semi-automated feature collection. 13
What if Pre-date LiDAR does not exist?
LiDAR market development Rapid growth 2004-2009 Pre-market growth availability? SGM can generate point cloud data for when LiDAR data did not exist.
SGM Workflow Stereo Imagery SGM Algorithm Dense Terrain Extraction
SGM Workflow
Semi-Global Matching Point Clouds
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Extract SGM Point Clouds: Workflow An alternative methodology was used to derive a Point Cloud layer using the accepted Semi Global Matching algorithm as another means of creating DSM s Automatic Elevations Extended uses the latest Semi-Global Matching algorithm for precise DSM creation producing an RGB encoded LAS file If an ISAT project does not already exist it can be created by exporting an LPS BLK file Load the project into ISAT and create models for the stereo pairs you wish to create LAS files for Open this saved project in ISAE-Extended and add the selected models for processing Submit the jobs to run local or distributed with Condor These LAS files created will be used to measure the volume of the spoil piles or quarry tailings for this project area
2013 Semi-Global Matching (SGM) Production-oriented dense matching solution Industry-standard method for dense surface correlation Same algorithm used in Leica s XPro generalized for frame data Support for DMC s I&II, RCD30, UltraCam Multi-core, multi-threaded (will deliver eight processing licenses) Outputs LAS files (point clouds) Applications City modeling True Ortho Forensics Visualization 21
Family, Delivered with Windows O/S Feature Collection (ISFC) MicroStation DTM Collection (ISDC) Stereo Display (ISSD) GeoMedia Stereo for GeoMedia (ISSG) Automatic Triangulation (ISAT) OrthoPro (ISOP) PixelQue (ISPQ) DTMQue (ISDQ) Automatic Elevations (ISAE) Photogrammetric Manager (ISPM) Satellite Triangulation (ISST) Automatic Elevations Extended (ISAE-Ext) PixelQue (ISPQ) Photogrammetric Manager (ISPM) GeoMedia Transaction Manager (GMTM) Feature Collection (ISFC) Automatic Elevations (ISAE)