scholarly journals Denoising of Laser Scanning Data Using Wavelet

2014 ◽  
Vol 12 ◽  
pp. 41-47 ◽  
Author(s):  
Petr Jašek ◽  
Martin Štroner
Keyword(s):  
Image Processing ◽  
Laser Scanning ◽  
Wavelet Transformation ◽  
Terrestrial Laser Scanning ◽  
Range Image ◽  
Regular Matrix ◽  
Post Processing ◽  
Spatial Coordinates ◽  
Measured Distance ◽  
Made In

Regarding the terrestrial laser scanning accuracy, one of the main problems is the noise in measured distance which is necessary for the spatial coordinates´ determination. In this paper the technique of using the wavelet transformation for the reduction of the noise in the laser scanning data is described. This method of filtration is made in “post processing” and due to this fact any changes in the measuring procedure in the field shouldn´t be done. The creation of the regular matrix is needed to apply image processing. This matrix then makes the range image. In the paper real and simulated efficiency tests of wavelet transformation, the final summary and advantages or disadvantages of this method are introduced.

scholarly journals Development of Image Processing for Crack Detection on Concrete Structures through Terrestrial Laser Scanning Associated with the Octree Structure

2018 ◽  
Vol 8 (12) ◽  
pp. 2373 ◽  
Author(s):  
Soojin Cho ◽  
Seunghee Park ◽  
Gichun Cha ◽  
Taekeun Oh
Keyword(s):  
Image Processing ◽  
Laser Scanning ◽  
Crack Detection ◽  
Surface Condition ◽  
Terrestrial Laser Scanning ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Morphological Operations ◽  
Cloud Data ◽  
Remote Sensing Technique

Terrestrial laser scanning (TLS) provides a rapid remote sensing technique to model 3D objects but can also be used to assess the surface condition of structures. In this study, an effective image processing technique is proposed for crack detection on images extracted from the octree structure of TLS data. To efficiently utilize TLS for the surface condition assessment of large structures, a process was constructed to compress the original scanned data based on the octree structure. The point cloud data obtained by TLS was converted into voxel data, and further converted into an octree data structure, which significantly reduced the data size but minimized the loss of resolution to detect cracks on the surface. The compressed data was then used to detect cracks on the surface using a combination of image processing algorithms. The crack detection procedure involved the following main steps: (1) classification of an image into three categories (i.e., background, structural joints and sediments, and surface) using K-means clustering according to color similarity, (2) deletion of non-crack parts on the surface using improved subtraction combined with median filtering and K-means clustering results, (3) detection of major crack objects on the surface based on Otsu’s binarization method, and (4) highlighting crack objects by morphological operations. The proposed technique was validated on a spillway wall of a concrete dam structure in South Korea. The scanned data was compressed up to 50% of the original scanned data, while showing good performance in detecting cracks with various shapes.

scholarly journals Range Image Technique for Change Analysis of Rock Slopes Using Dense Point Cloud Data

2018 ◽  
Vol 10 (11) ◽  
pp. 1792 ◽  
Author(s):  
Yueqian Shen ◽  
Jinguo Wang ◽  
Roderik Lindenbergh ◽  
Bas Hofland ◽  
Vagner G. Ferreira
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Range Image ◽  
Point Cloud Data ◽  
Rock Slopes ◽  
Change Analysis ◽  
Cloud Data ◽  
Before And After ◽  
Image Technique

The use of a terrestrial laser scanner is examined to measure the changes of rock slopes subject to a wave attack test. Real scenarios are simulated in a water flume facility using a wave attack experiment representing a storm of 3000 waves. The stability of two rock slopes of different steepness was evaluated under the set conditions. For quantification of the changes of the slopes after the wave attack test, terrestrial laser scanning was used to acquire dense 3D point cloud data sampling for slope geometries before and after the wave attack experiment. After registration of the two scans, representing situations before and after the wave attack, the cloud-to-cloud distance was determined to identify areas in the slopes that were affected. Then, a range image technique was introduced to generate a raster image to facilitate a change analysis. Using these raster images, volume change was estimated as well. The results indicate that the area around the artificial coast line is most strongly affected by wave attacks. Another interesting phenomenon considers the change in transport direction of the rocks between the two slopes: from seaward transport for the steeper slope to landward transport for the milder slope. Using the range image technique, the work in this article shows that terrestrial laser scanning is an effective and feasible method for change analysis of long and narrow rock slopes.

scholarly journals Assessing the capability of terrestrial laser scanning for monitoring slow moving landslides

2009 ◽  
Vol 9 (6) ◽  
pp. 1921-1928 ◽  
Author(s):  
A. Prokop ◽  
H. Panholzer
Keyword(s):  
Laser Scanning ◽  
Mass Movement ◽  
Terrestrial Laser Scanning ◽  
Movement Patterns ◽  
Slope Movement ◽  
Post Processing ◽  
Cloud Data ◽  
Movement Rates ◽  
Point Density ◽  
Processing Steps

Abstract. Digital elevation models (DEM) are widely used to determine characteristics of mass movement processes such as accumulation and deposition of material, volume estimates or the orientation of discontinuities. To create such DEMs point cloud data is provided by terrestrial laser scanning (TLS) and recently used for analysis of mass movements. Therefore the reliability of TLS data was investigated in a comparative study with tachymetry. The main focus was on the possibility of determining movement patterns of landslides <100 mm. Therefore, several post processing steps are needed and the reliability of those were analyzed. The post processing steps that were investigated include: (1) The registration process is a crucial step considering long term TLS monitoring of an object and can be significantly improved using an iterative closest point (ICP) algorithm; (2) Filtering methods are necessary to create DEMs in order to separate favored laser points on the terrain surface (ground points) from topographically irrelevant points (non-ground-points). Therefore GIS tools were applied. Surfaces with and without vegetation cover were differentiated; (3) Displacement vectors are used to determine slope movement rates. They were created from TLS data after the computation of true orthophotos. Using the methodology presented it was not possible to determine movement rates <50 mm per period. However, if the quality of the point density is described and areas with very low point density are detected, reliable conclusions can be made regarding slope movement patterns and erosion and deposition of material for changes <100 mm for the investigated slope.

The quantitative comparison of experimental and simulated diffraction contrast images

1995 ◽  
Vol 53 ◽  
pp. 102-103
Author(s):  
Stuart McKernan
Keyword(s):  
Image Processing ◽  
Personal Computer ◽  
Close Agreement ◽  
Quantitative Comparison ◽  
Image Simulation ◽  
Computing Power ◽  
Diffraction Contrast ◽  
Simulated Images ◽  
Made In

For many years the concept of quantitative diffraction contrast experiments might have consisted of the determination of dislocation Burgers vectors using a g.b = 0 criterion from several different 2-beam images. Since the advent of the personal computer revolution, the available computing power for performing image-processing and image-simulation calculations is enormous and ubiquitous. Several programs now exist to perform simulations of diffraction contrast images using various approximations. The most common approximations are the use of only 2-beams or a single systematic row to calculate the image contrast, or calculating the image using a column approximation. The increasing amount of literature showing comparisons of experimental and simulated images shows that it is possible to obtain very close agreement between the two images; although the choice of parameters used, and the assumptions made, in performing the calculation must be properly dealt with. The simulation of the images of defects in materials has, in many cases, therefore become a tractable problem.

scholarly journals Melite Civitas Romana in 3D: Virtualization Project of the Archaeological Park and Museum of the Domus Romana of Rabat, Malta

2021 ◽  
Vol 7 (1) ◽  
pp. 51-83
Author(s):  
Davide Tanasi ◽  
Stephan Hassam ◽  
Kaitlyn Kingsland ◽  
Paolo Trapani ◽  
Matthew King ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Structured Light ◽  
Terrestrial Laser Scanning ◽  
Archaeological Site ◽  
South Florida ◽  
Virtual Museum ◽  
Current State ◽  
Structured Light Scanning ◽  
The University ◽  
Archaeological Excavations

Abstract The archaeological site of the Domus Romana in Rabat, Malta was excavated almost 100 years ago yielding artefacts from the various phases of the site. The Melite Civitas Romana project was designed to investigate the domus, which may have been the home of a Roman Senator, and its many phases of use. Pending planned archaeological excavations designed to investigate the various phases of the site, a team from the Institute for Digital Exploration from the University of South Florida carried out a digitization campaign in the summer of 2019 using terrestrial laser scanning and aerial digital photogrammetry to document the current state of the site to provide a baseline of documentation and plan the coming excavations. In parallel, structured light scanning and photogrammetry were used to digitize 128 artefacts in the museum of the Domus Romana to aid in off-site research and create a virtual museum platform for global dissemination.

scholarly journals Terrestrial Laser Scanning for Vegetation Analyses with a Special Focus on Savannas

2021 ◽  
Vol 13 (3) ◽  
pp. 507
Author(s):  
Tasiyiwa Priscilla Muumbe ◽  
Jussi Baade ◽  
Jenia Singh ◽  
Christiane Schmullius ◽  
Christian Thau
Keyword(s):  
Remote Sensing ◽  
Vegetation Structure ◽  
Laser Scanning ◽  
Spatial Scales ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Parameter Extraction ◽  
Airborne Lidar ◽  
Special Focus ◽  
Vegetation Parameter

Savannas are heterogeneous ecosystems, composed of varied spatial combinations and proportions of woody and herbaceous vegetation. Most field-based inventory and remote sensing methods fail to account for the lower stratum vegetation (i.e., shrubs and grasses), and are thus underrepresenting the carbon storage potential of savanna ecosystems. For detailed analyses at the local scale, Terrestrial Laser Scanning (TLS) has proven to be a promising remote sensing technology over the past decade. Accordingly, several review articles already exist on the use of TLS for characterizing 3D vegetation structure. However, a gap exists on the spatial concentrations of TLS studies according to biome for accurate vegetation structure estimation. A comprehensive review was conducted through a meta-analysis of 113 relevant research articles using 18 attributes. The review covered a range of aspects, including the global distribution of TLS studies, parameters retrieved from TLS point clouds and retrieval methods. The review also examined the relationship between the TLS retrieval method and the overall accuracy in parameter extraction. To date, TLS has mainly been used to characterize vegetation in temperate, boreal/taiga and tropical forests, with only little emphasis on savannas. TLS studies in the savanna focused on the extraction of very few vegetation parameters (e.g., DBH and height) and did not consider the shrub contribution to the overall Above Ground Biomass (AGB). Future work should therefore focus on developing new and adjusting existing algorithms for vegetation parameter extraction in the savanna biome, improving predictive AGB models through 3D reconstructions of savanna trees and shrubs as well as quantifying AGB change through the application of multi-temporal TLS. The integration of data from various sources and platforms e.g., TLS with airborne LiDAR is recommended for improved vegetation parameter extraction (including AGB) at larger spatial scales. The review highlights the huge potential of TLS for accurate savanna vegetation extraction by discussing TLS opportunities, challenges and potential future research in the savanna biome.

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