True Orthophoto Generation from Aerial Frame Images and LiDAR Data: An Update
Image spectral and Light Detection and Ranging (LiDAR) positional information can be related through the orthophoto generation process. Orthophotos have a uniform scale and represent all objects in their correct planimetric locations. However, orthophotos generated using conventional methods suffer...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-04-01
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| Series: | Remote Sensing |
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| Online Access: | http://www.mdpi.com/2072-4292/10/4/581 |
| _version_ | 1819002625690959872 |
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| author | Hamid Gharibi Ayman Habib |
| author_facet | Hamid Gharibi Ayman Habib |
| author_sort | Hamid Gharibi |
| collection | DOAJ |
| description | Image spectral and Light Detection and Ranging (LiDAR) positional information can be related through the orthophoto generation process. Orthophotos have a uniform scale and represent all objects in their correct planimetric locations. However, orthophotos generated using conventional methods suffer from an artifact known as the double-mapping effect that occurs in areas occluded by tall objects. The double-mapping problem can be resolved through the commonly known true orthophoto generation procedure, in which an occlusion detection process is incorporated. This paper presents a review of occlusion detection methods, from which three techniques are compared and analyzed using experimental results. The paper also describes a framework for true orthophoto production based on an angle-based occlusion detection method. To improve the performance of the angle-based technique, two modifications to this method are introduced. These modifications, which aim at resolving false visibilities reported within the angle-based occlusion detection process, are referred to as occlusion extension and radial section overlap. A weighted averaging approach is also proposed to mitigate the seamline effect and spectral dissimilarity that may appear in true orthophoto mosaics. Moreover, true orthophotos generated from high-resolution aerial images and high-density LiDAR data using the updated version of angle-based methodology are illustrated for two urban study areas. To investigate the potential of image matching techniques in producing true orthophotos and point clouds, a comparison between the LiDAR-based and image-matching-based true orthophotos and digital surface models (DSMs) for an urban study area is also presented in this paper. Among the investigated occlusion detection methods, the angle-based technique demonstrated a better performance in terms of output and running time. The LiDAR-based true orthophotos and DSMs showed higher qualities compared to their image-matching-based counterparts which contain artifacts/noise along building edges. |
| first_indexed | 2024-12-20T23:08:05Z |
| format | Article |
| id | doaj.art-994af87baaf24fde8b07d68c1653707f |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-20T23:08:05Z |
| publishDate | 2018-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-994af87baaf24fde8b07d68c1653707f2022-12-21T19:23:49ZengMDPI AGRemote Sensing2072-42922018-04-0110458110.3390/rs10040581rs10040581True Orthophoto Generation from Aerial Frame Images and LiDAR Data: An UpdateHamid Gharibi0Ayman Habib1School of Civil Engineering, University College Dublin, Newstead, Belfield, Dublin 4, IrelandLyles School of Civil Engineering, Purdue University, 550 Stadium Mall Drive, West Lafayette, IN 47907-2051, USAImage spectral and Light Detection and Ranging (LiDAR) positional information can be related through the orthophoto generation process. Orthophotos have a uniform scale and represent all objects in their correct planimetric locations. However, orthophotos generated using conventional methods suffer from an artifact known as the double-mapping effect that occurs in areas occluded by tall objects. The double-mapping problem can be resolved through the commonly known true orthophoto generation procedure, in which an occlusion detection process is incorporated. This paper presents a review of occlusion detection methods, from which three techniques are compared and analyzed using experimental results. The paper also describes a framework for true orthophoto production based on an angle-based occlusion detection method. To improve the performance of the angle-based technique, two modifications to this method are introduced. These modifications, which aim at resolving false visibilities reported within the angle-based occlusion detection process, are referred to as occlusion extension and radial section overlap. A weighted averaging approach is also proposed to mitigate the seamline effect and spectral dissimilarity that may appear in true orthophoto mosaics. Moreover, true orthophotos generated from high-resolution aerial images and high-density LiDAR data using the updated version of angle-based methodology are illustrated for two urban study areas. To investigate the potential of image matching techniques in producing true orthophotos and point clouds, a comparison between the LiDAR-based and image-matching-based true orthophotos and digital surface models (DSMs) for an urban study area is also presented in this paper. Among the investigated occlusion detection methods, the angle-based technique demonstrated a better performance in terms of output and running time. The LiDAR-based true orthophotos and DSMs showed higher qualities compared to their image-matching-based counterparts which contain artifacts/noise along building edges.http://www.mdpi.com/2072-4292/10/4/581photogrammetryLiDARdata fusionocclusion detectiontrue orthophotourban mapping |
| spellingShingle | Hamid Gharibi Ayman Habib True Orthophoto Generation from Aerial Frame Images and LiDAR Data: An Update Remote Sensing photogrammetry LiDAR data fusion occlusion detection true orthophoto urban mapping |
| title | True Orthophoto Generation from Aerial Frame Images and LiDAR Data: An Update |
| title_full | True Orthophoto Generation from Aerial Frame Images and LiDAR Data: An Update |
| title_fullStr | True Orthophoto Generation from Aerial Frame Images and LiDAR Data: An Update |
| title_full_unstemmed | True Orthophoto Generation from Aerial Frame Images and LiDAR Data: An Update |
| title_short | True Orthophoto Generation from Aerial Frame Images and LiDAR Data: An Update |
| title_sort | true orthophoto generation from aerial frame images and lidar data an update |
| topic | photogrammetry LiDAR data fusion occlusion detection true orthophoto urban mapping |
| url | http://www.mdpi.com/2072-4292/10/4/581 |
| work_keys_str_mv | AT hamidgharibi trueorthophotogenerationfromaerialframeimagesandlidardataanupdate AT aymanhabib trueorthophotogenerationfromaerialframeimagesandlidardataanupdate |