Poster + Paper
20 September 2020 Comparison between two radiometric calibration methods applied to UAV multispectral images
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Conference Poster
Abstract
There are many advantages of using unmanned aerial vehicles (UAVs) in remote sensing but when using radiometrically corrected multispectral images. This study focuses on two techniques of obtain a multispectral orthomosaic with suitable radiometric quality considering a day period with minor variations in illumination and clouds. The first technique comprises a radiometric block adjustment combined with empirical line whilst the second technique uses only empirical line. Field measurements with spectrometers were used to assess the techniques. The obtained results show that the radiometric block adjustment presented better results when compared to the radiometric reference targets and its calculated Hemispherical Conical Reflectance Factor (HCRF) from the spectrometer. However, the root mean square error (RMSE), normalized root mean square error (NRMSE) and mean absolute percentage error (MAPE) were similar in both cases, showing that the two proposed workflows can generate multispectral mosaics with acceptable radiometric quality for a period in which illumination conditions are stable. Images difference between each band was produced showing that there was a stronger variation of pixels in the higher slope region, which indicates that additional corrections beyond empirical line are needed in these situations
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
L. R. Porto, N. N. Imai, A. Berveglieri, G. T. Miyoshi, É. A. S. Moriya, A. M. G. Tommaselli, and E. Honkavaara "Comparison between two radiometric calibration methods applied to UAV multispectral images", Proc. SPIE 11533, Image and Signal Processing for Remote Sensing XXVI, 115331U (20 September 2020); https://doi.org/10.1117/12.2579346
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KEYWORDS
Multispectral imaging

Unmanned aerial vehicles

Calibration

Reflectivity

Cameras

Spectroscopy

Radiometric corrections

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