Title
Automatic Hotspot and Sun Glint Detection in UAV Multispectral Images.
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.
Year
DOI
Venue
2017
10.3390/s17102352
SENSORS
Keywords
Field
DocType
UAV,hotspot,sun glint,image preprocessing,photogrammetry,remote sensing,flight planning and control,software development
Computer vision,Photogrammetry,Ground sample distance,Remote sensing,Multispectral image,Flight planning,Remote sensing application,Digital elevation model,Artificial intelligence,Pixel,Engineering,3D reconstruction
Journal
Volume
Issue
ISSN
17
10.0
1424-8220
Citations 
PageRank 
References 
2
0.40
9
Authors
4