Standardized spectral and radiometric calibration of consumer cameras



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Burggraaff, Oliver and Schmidt, Norbert and Zamorano Calvo, Jaime and Pauly, Klaas and Pascual Ramírez, Sergio and Tapia Ayuga, Carlos and Spyrakos, Evangelos and Snik, Frans (2019) Standardized spectral and radiometric calibration of consumer cameras. Optics express, 27 (14). pp. 19075-19101. ISSN 1094-4087

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Consumer cameras, particularly onboard smartphones and UAVs, are now commonly used as scientific instruments. However, their data processing pipelines are not optimized for quantitative radiometry and their calibration is more complex than that of scientific cameras. The lack of a standardized calibration methodology limits the interoperability between devices and, in the ever-changing market, ultimately the lifespan of projects using them. We present a standardized methodology and database (SPECTACLE) for spectral and radiometric calibrations of consumer cameras, including linearity, bias variations, read-out noise, dark current, ISO speed and gain, flat-field, and RGB spectral response. This includes golden standard ground-truth methods and do-it-yourself methods suitable for non-experts. Applying this methodology to seven popular cameras, we found high linearity in RAW but not JPEG data, inter-pixel gain variations >400% correlated with large-scale bias and read-out noise patterns, non-trivial ISO speed normalization functions, flat-field correction factors varying by up to 2.79 over the field of view, and both similarities and differences in spectral response. Moreover, these results differed wildly between camera models, highlighting the importance of standardization and a centralized database.

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© 2019 Optical Society of America. Funding by Horizon 2020 Framework Programme (grant nr. 776480, MONOCLE and grant nr. 824603, ACTION). The authors wish to thank Molly and Chris MacLellan of the NERC Field Spectroscopy Facility for experimental help and invaluable insights in the flat-field and spectral response measurements. Figure 1 was drawn using Data analysis and visualization were done using the AstroPy, ExifRead, Matplotlib, NumPy, RawPy, and SciPy libraries for Python. Finally, the authors wish to thank the two anonymous reviewers for their thorough and constructive reviews. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 776480.

Uncontrolled Keywords:Digital cameras; Color; Sensitivity; Smartphones; Methodology; Vegetation; Aerosols
Subjects:Sciences > Physics > Atmospheric physics
ID Code:57646
Deposited On:22 Nov 2019 11:27
Last Modified:22 Nov 2019 12:38

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