Next Article in Journal
Application of Semi-Automated Filter to Improve Waveform Lidar Sub-Canopy Elevation Model
Next Article in Special Issue
Development of a UAV-LiDAR System with Application to Forest Inventory
Previous Article in Journal
Tsunami Arrival Detection with High Frequency (HF) Radar
Previous Article in Special Issue
An Automated Technique for Generating Georectified Mosaics from Ultra-High Resolution Unmanned Aerial Vehicle (UAV) Imagery, Based on Structure from Motion (SfM) Point Clouds
Remote Sens. 2012, 4(5), 1462-1493; doi:10.3390/rs4051462
Article

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

*  and
Received: 28 March 2012 / Revised: 20 April 2012 / Accepted: 4 May 2012 / Published: 18 May 2012
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs) based Remote Sensing)

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.
Keywords: UAV; sensor correction; radiometric correction UAV; sensor correction; radiometric correction
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.

Share & Cite This Article

Further Mendeley | CiteULike
Export to BibTeX |
EndNote
MDPI and ACS Style

Kelcey, J.; Lucieer, A. Sensor Correction of a 6-Band Multispectral Imaging Sensor for UAV Remote Sensing. Remote Sens. 2012, 4, 1462-1493.

View more citation formats

Article Metrics

For more information on the journal, click here

Comments

Cited By

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert