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Sensors 2017, 17(10), 2352; https://doi.org/10.3390/s17102352

Automatic Hotspot and Sun Glint Detection in UAV Multispectral Images

1
Higher Polytechnic School of Ávila, University of Salamanca, 05003 Ávila, Spain
2
Institute for Regional Development (IDR), University of Castilla-La Mancha, Campus Universitario s/n, 02071 Albacete, Spain
3
Regional Centre of Water Research (CREA), University of Castilla-La Mancha, Carretera de las Peñas km 3.2, 02071 Albacete, Spain
*
Author to whom correspondence should be addressed.
Received: 13 August 2017 / Revised: 12 October 2017 / Accepted: 13 October 2017 / Published: 15 October 2017
(This article belongs to the Special Issue UAV or Drones for Remote Sensing Applications)
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Abstract

Last advances in sensors, photogrammetry and computer vision have led to high-automation levels of 3D reconstruction processes for generating dense models and multispectral orthoimages from Unmanned Aerial Vehicle (UAV) images. However, these cartographic products are sometimes blurred and degraded due to sun reflection effects which reduce the image contrast and colour fidelity in photogrammetry and the quality of radiometric values in remote sensing applications. This paper proposes an automatic approach for detecting sun reflections problems (hotspot and sun glint) in multispectral images acquired with an Unmanned Aerial Vehicle (UAV), based on a photogrammetric strategy included in a flight planning and control software developed by the authors. In particular, two main consequences are derived from the approach developed: (i) different areas of the images can be excluded since they contain sun reflection problems; (ii) the cartographic products obtained (e.g., digital terrain model, orthoimages) and the agronomical parameters computed (e.g., normalized vegetation index-NVDI) are improved since radiometric defects in pixels are not considered. Finally, an accuracy assessment was performed in order to analyse the error in the detection process, getting errors around 10 pixels for a ground sample distance (GSD) of 5 cm which is perfectly valid for agricultural applications. This error confirms that the precision in the detection of sun reflections can be guaranteed using this approach and the current low-cost UAV technology. View Full-Text
Keywords: UAV; hotspot; sun glint; image preprocessing; photogrammetry; remote sensing; flight planning and control; software development UAV; hotspot; sun glint; image preprocessing; photogrammetry; remote sensing; flight planning and control; software development
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Ortega-Terol, D.; Hernandez-Lopez, D.; Ballesteros, R.; Gonzalez-Aguilera, D. Automatic Hotspot and Sun Glint Detection in UAV Multispectral Images. Sensors 2017, 17, 2352.

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