scholarly journals BLOCK ADJUSTMENT AND IMAGE MATCHING OF WORLDVIEW-3 STEREO PAIRS AND ACCURACY EVALUATION

2018 ◽  
Vol XLII-3 ◽  
pp. 2473-2477
Author(s):  
C. Zuo ◽  
X. Xiao ◽  
Q. Hou ◽  
B. Li
Keyword(s):  
Image Matching ◽  
Point Cloud ◽  
Large Scale ◽  
Laser Scanner ◽  
Stereo Image ◽  
Topographic Mapping ◽  
Accuracy Evaluation ◽  
Airborne Laser Scanner ◽  
Earth Observation Satellite ◽  
Stereo Image Matching

WorldView-3, as a high-resolution commercial earth observation satellite, which is launched by Digital Global, provides panchromatic imagery of 0.31&amp;thinsp;m resolution. The positioning accuracy is less than 3.5 meter CE90 without ground control, which can use for large scale topographic mapping. This paper presented the block adjustment for WorldView-3 based on RPC model and achieved the accuracy of 1&amp;thinsp;:&amp;thinsp;2000 scale topographic mapping with few control points. On the base of stereo orientation result, this paper applied two kinds of image matching algorithm for DSM extraction: LQM and SGM. Finally, this paper compared the accuracy of the point cloud generated by the two image matching methods with the reference data which was acquired by an airborne laser scanner.<br> The results showed that the RPC adjustment model of WorldView-3 image with small number of GCPs could satisfy the requirement of Chinese Surveying and Mapping regulations for 1&amp;thinsp;:&amp;thinsp;2000 scale topographic maps. And the point cloud result obtained through WorldView-3 stereo image matching had higher elevation accuracy, the RMS error of elevation for bare ground area is 0.45&amp;thinsp;m, while for buildings the accuracy can almost reach 1 meter.

scholarly journals UAV and terrestrial laser scanner data processing for large scale topographic mapping

2020 ◽  
Vol 50 ◽  
pp. 63-73
Author(s):  
Ganbold Ulziisaikhan ◽  
Dash Oyuntsetseg
Keyword(s):  
Data Processing ◽  
Spatial Data ◽  
Large Scale ◽  
Laser Scanner ◽  
Measurement Technology ◽  
Topographic Mapping ◽  
Terrestrial Laser Scanner ◽  
Scanner Data ◽  
Processing Scheme ◽  
Digital Elevation

Integrating spatial data from different sources results in visualization, which is the last step in the process of digital basic topographic map creation. Digital elevation model and visualization will used for geomorphological mapping, geospatial database, urban planning and etc. Large scale topographic mapping in the world countries is really a prominent challenge in geospatial industries today. The purpose of this work is to integrate laser scanner data with the ones generated by aerial photogrammetry from UAV, to produce detailed maps that can used by geodetic engineers to optimize their analysis. In addition, terrestrial - based LiDAR scans and UAV photogrammetric data were collected in Sharga hill in the north zone of Mongolia. In this paper, different measurement technology and processing software systems combined for topographic mapping in the data processing scheme. UTM (Universal Transverse Mercator) projected coordinate system calculated in WGS84 reference ellipsoid. Feature compilation involving terrestrial laser scanner data and UAV data will integrated to offer Digital Elevation Models (DEM) as the main interest of the topographic mapping activity. Used UAV generate high-resolution orthomosaics and detailed 3D models of areas where no data, are available. That result issued to create topographic maps with a scale of 1:1000 of geodetic measurements. Preliminary results indicate that discontinuity data collection from UAV closely matches the data collected using laser scanner.

Detection of Building in Airborne Laser Scanner Data and Aerial Images

2012 ◽  
Vol 11 ◽  
pp. 7-13
Author(s):  
Dilli Raj Bhandari
Keyword(s):  
Point Cloud ◽  
Laser Scanner ◽  
Aerial Images ◽  
Spectral Information ◽  
Surface Model ◽  
World Population ◽  
Data Sets ◽  
Scanner Data ◽  
Airborne Laser Scanner ◽  
Airborne Laser

The automatic extraction of the objects from airborne laser scanner data and aerial images has been a topic of research for decades. Airborne laser scanner data are very efficient source for the detection of the buildings. Half of the world population lives in urban/suburban areas, so detailed, accurate and up-to-date building information is of great importance to every resident, government agencies, and private companies. The main objective of this paper is to extract the features for the detection of building using airborne laser scanner data and aerial images. To achieve this objective, a method of integration both LiDAR and aerial images has been explored: thus the advantages of both data sets are utilized to derive the buildings with high accuracy. Airborne laser scanner data contains accurate elevation information in high resolution which is very important feature to detect the elevated objects like buildings and the aerial image has spectral information and this spectral information is an appropriate feature to separate buildings from the trees. Planner region growing segmentation of LiDAR point cloud has been performed and normalized digital surface model (nDSM) is obtained by subtracting DTM from the DSM. Integration of the nDSM, aerial images and the segmented polygon features from the LiDAR point cloud has been carried out. The optimal features for the building detection have been extracted from the integration result. Mean height value of the nDSM, Normalized difference vegetation index (NDVI) and the standard deviation of the nDSM are the effective features. The accuracy assessment of the classification results obtained using the calculated attributes was done. Assessment result yielded an accuracy of almost 92 % explaining the features which are extracted by integrating the two data sets was large extent, effective for the automatic detection of the buildings.

Research on Stereo Image Acquisition Technology of 3D Printing

2014 ◽  
Vol 644-650 ◽  
pp. 2656-2660
Author(s):  
Yao Cheng ◽  
Guang Xue Chen ◽  
Chen Chen ◽  
Jiang Ping Yuan
Keyword(s):  
3D Printing ◽  
Point Cloud ◽  
Image Acquisition ◽  
Laser Scanner ◽  
Stereo Image ◽  
Object Model ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Engineering Software ◽  
Hand Model

In the process of 3D printing, stereo image acquisition is the basis and premise of 3D modeling so that it’s important to study the acquisition methods and techniques. This paper will study the process of point cloud data acquisition of a hand model by using handheld laser scanner REVscan, and processed by the reverse engineering software Geomagic Studio. Using the object model captured, we can greatly improve the efficiency and accuracy, as well as reduce the cycle of the 3D printing. This will help achieve the transmission of 3D printing data without geographical restrictions, in which truly realize the concept "What You See Is What You Get".

scholarly journals Digital Surface Model Interpolation Based on 3D Mesh Models

2018 ◽  
Vol 11 (1) ◽  
pp. 24 ◽  
Author(s):  
Soohyeon Kim ◽  
Sooahm Rhee ◽  
Taejung Kim
Keyword(s):  
Image Matching ◽  
3D Visualization ◽  
Interpolation Method ◽  
Stereo Image ◽  
Distribution Model ◽  
Surface Model ◽  
Digital Surface Model ◽  
3D Mesh ◽  
Stereo Image Matching ◽  
Mesh Models

A digital surface model (DSM) is an important geospatial infrastructure used in various fields. In this paper, we deal with how to improve the quality of DSMs generated from stereo image matching. During stereo image matching, there are outliers due to mismatches, and non-matching regions due to match failure. Such outliers and non-matching regions have to be corrected accurately and efficiently for high-quality DSM generation. This process has been performed by applying a local distribution model, such as inverse distance weight (IDW), or by forming a triangulated irregular network (TIN). However, if the area of non-matching regions is large, it is not trivial to interpolate elevation values using neighboring cells. In this study, we proposed a new DSM interpolation method using a 3D mesh model, which is more robust to outliers and large holes. We compared mesh-based DSM with IDW-based DSM and analyzed the characteristics of each. The accuracy of the mesh-based DSM was a 2.80 m root mean square error (RMSE), while that for the IDW-based DSM was 3.22 m. While the mesh-based DSM successfully removed empty grid cells and outliers, the IDW-based DSM had sharper object boundaries. Because of the nature of surface reconstruction, object boundaries appeared smoother on the mesh-based DSM. We further propose a method of integrating the two DSMs. The integrated DSM maintains the sharpness of object boundaries without significant accuracy degradation. The contribution of this paper is the use of 3D mesh models (which have mainly been used for 3D visualization) for efficient removal of outliers and non-matching regions without a priori knowledge of surface types.

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