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Color-guided enhancement of airborne laser scanning data

: Keskin, Göksu; Gross, Wolfgang; Middelmann, Wolfgang

Postprint urn:nbn:de:0011-n-4769825 (635 KByte PDF)
MD5 Fingerprint: 9ee1739c6bc280b3da511064451a80db
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Created on: 14.12.2017

Institute of Electrical and Electronics Engineers -IEEE-; IEEE Geoscience and Remote Sensing Society:
IEEE International Geoscience & Remote Sensing Symposium 2017. Proceedings : July 23-28, 2017, Fort Worth, Texas, USA
Piscataway, NJ: IEEE, 2017
ISBN: 978-1-5090-4951-6
ISBN: 978-1-5090-4950-9
ISBN: 978-1-5090-4952-3
International Geoscience and Remote Sensing Symposium (IGARSS) <37, 2017, Fort Worth/Tex.>
Conference Paper, Electronic Publication
Fraunhofer IOSB ()
lidar depth enhancement; JBF; anisotropic diffusion

This paper suggests using color-guided depth enhancement algorithms of computer vision to improve the resolution of airborne laser scanning (ALS) point clouds for remote sensing applications. We use co-registered high resolution color images with nadir view to enhance the ALS data; and perform quantitative evaluation in form of RMSE considering the whole depth image as well as the depth discontinuities only. Investigated methods include joint bilateral filtering, Markov Random Field (MRF) optimization with first and second order smoothness terms, and anisotropic diffusion. RMSE results on discontinuities indicate that detail improvement performance of the selected methods on the depth discontinuities is not on a satisfactory level for airborne data. Anisotropic diffusion and MRF optimization are promising to provide better results with further adjustments on the smoothness terms.