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Sensor Correction of a 6-Band Multispectral Imaging Sensor for UAV Remote Sensing

Citation

Kelcey, J and Lucieer, A, Sensor Correction of a 6-Band Multispectral Imaging Sensor for UAV Remote Sensing, Remote Sensing, 4, (5) pp. 1462-1493. ISSN 2072-4292 (2012) [Refereed Article]


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Copyright Statement

Licensed under the Creative Commons Attribution 3.0 Unported (CC BY 3.0) http://creativecommons.org/licenses/by/3.0/

DOI: doi:10.3390/rs4051462

Abstract

Unmanned aerial vehicles (UAVs) represent a quickly evolving technology, broadening the availability of remote sensing tools to small-scale research groups across a variety of scientific fields. Development of UAV platforms requires broad technical skills covering platform development, data post-processing, and image analysis. UAV development is constrained by a need to balance technological accessibility, flexibility in application and quality in image data. In this study, the quality of UAV imagery acquired by a miniature 6-band multispectral imaging sensor was improved through the application of practical image-based sensor correction techniques. Three major components of sensor correction were focused upon: noise reduction, sensor-based modification of incoming radiance, and lens distortion. Sensor noise was reduced through the use of dark offset imagery. Sensor modifications through the effects of filter transmission rates, the relative monochromatic efficiency of the sensor and the effects of vignetting were removed through a combination of spatially/spectrally dependent correction factors. Lens distortion was reduced through the implementation of the Brown–Conrady model. Data post-processing serves dual roles in data quality improvement, and the identification of platform limitations and sensor idiosyncrasies. The proposed corrections improve the quality of the raw multispectral imagery, facilitating subsequent quantitative image analysis.

Item Details

Item Type:Refereed Article
Research Division:Earth Sciences
Research Group:Physical Geography and Environmental Geoscience
Research Field:Physical Geography and Environmental Geoscience not elsewhere classified
Objective Division:Environment
Objective Group:Ecosystem Assessment and Management
Objective Field:Ecosystem Assessment and Management at Regional or Larger Scales
Author:Kelcey, J (Mr Joshua Kelcey)
Author:Lucieer, A (Associate Professor Arko Lucieer)
ID Code:79082
Year Published:2012
Web of Science® Times Cited:49
Deposited By:Geography and Environmental Studies
Deposited On:2012-08-16
Last Modified:2013-04-26
Downloads:440 View Download Statistics

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