Investigation of parallax issues for multi-lens multispectral camera band co-registration

J. P. Jhan, J. Y. Rau, N. Haala, M. Cramer

研究成果: Conference article

5 引文 (Scopus)

摘要

The multi-lens multispectral cameras (MSCs), such as Micasense Rededge and Parrot Sequoia, can record multispectral information by each separated lenses. With their lightweight and small size, which making they are more suitable for mounting on an Unmanned Aerial System (UAS) to collect high spatial images for vegetation investigation. However, due to the multi-sensor geometry of multilens structure induces significant band misregistration effects in original image, performing band co-registration is necessary in order to obtain accurate spectral information. A robust and adaptive band-to-band image transform (RABBIT) is proposed to perform band co-registration of multi-lens MSCs. First is to obtain the camera rig information from camera system calibration, and utilizes the calibrated results for performing image transformation and lens distortion correction. Since the calibration uncertainty leads to different amount of systematic errors, the last step is to optimize the results in order to acquire a better co-registration accuracy. Due to the potential issues of parallax that will cause significant band misregistration effects when images are closer to the targets, four datasets thus acquired from Rededge and Sequoia were applied to evaluate the performance of RABBIT, including aerial and close-range imagery. From the results of aerial images, it shows that RABBIT can achieve sub-pixel accuracy level that is suitable for the band coregistration purpose of any multi-lens MSC. In addition, the results of close-range images also has same performance, if we focus on the band co-registration on specific target for 3D modelling, or when the target has equal distance to the camera. |

原文English
頁(從 - 到)157-163
頁數7
期刊International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
42
發行號2W6
DOIs
出版狀態Published - 2017 八月 23
事件4th ISPRS International Conference on Unmanned Aerial Vehicles in Geomatics, UAV-g 2017 - Bonn, Germany
持續時間: 2017 九月 42017 九月 7

指紋

Lenses
Cameras
Antennas
transform
Calibration
Systematic errors
Mountings
calibration
registration
Pixels
performance
Geometry
Sensors
pixel
mathematics
uncertainty
imagery
sensor
cause
geometry

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Geography, Planning and Development

引用此文

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