CORRECTION AND DENSIFICATION OF UAS-BASED PHOTOGRAMMETRIC THERMAL POINT CLOUD
| Autor: | Ozgun Akcay, Oya Erenoglu, Ramazan Cuneyt Erenoglu |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
lcsh:Applied optics. Photonics
business.product_category 010504 meteorology & atmospheric sciences Image quality Feature extraction Point cloud 0211 other engineering and technologies Image processing 02 engineering and technology lcsh:Technology 01 natural sciences Digital image 0202 electrical engineering electronic engineering information engineering Computer vision Astrophysics::Galaxy Astrophysics Digital camera Remote sensing 021101 geological & geomatics engineering 0105 earth and related environmental sciences lcsh:T business.industry Orthophoto lcsh:TA1501-1820 020207 software engineering Geography Photogrammetry lcsh:TA1-2040 020201 artificial intelligence & image processing Artificial intelligence lcsh:Engineering (General). Civil engineering (General) business |
| Zdroj: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLI-B3, Pp 163-166 (2016) |
| ISSN: | 2194-9034 |
| Popis: | Photogrammetric processing algorithms can suffer problems due to either the initial image quality (noise, low radiometric quality, shadows and so on) or to certain surface materials (shiny or textureless objects). This can result in noisy point clouds and/or difficulties in feature extraction. Specifically, dense point clouds which are generated with photogrammetric method using a lightweight thermal camera, are more noisy and sparse than the point clouds of high-resolution digital camera images. In this paper, new method which produces more reliable and dense thermal point cloud using the sparse thermal point cloud and high resolution digital point cloud was considered. Both thermal and digital images were obtained with UAS (Unmanned Aerial System) based lightweight Optris PI 450 and Canon EOS 605D camera images. Thermal and digital point clouds, and orthophotos were produced using photogrammetric methods. Problematic thermal point cloud was transformed to a high density thermal point cloud using image processing methods such as rasterizing, registering, interpolation and filling. The results showed that the obtained thermal point cloud - up to chosen processing parameters - was 87% more densify than the original point cloud. The second improvement was gained at the height accuracy of the thermal point cloud. New densified point cloud has more consistent elevation model while the original thermal point cloud shows serious deviations from the expected surface model. |
| Databáze: | OpenAIRE |
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