Standardized spectral and radiometric calibration of consumer cameras

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 calib...

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Detalles Bibliográficos
Autores: Burggraaff, Oliver, Schmidt, Norbert, Zamorano Calvo, Jaime, Pauly, Klaas, Pascual Ramírez, Sergio, Tapia Ayuga, Carlos, Spyrakos, Evangelos, Snik, Frans
Tipo de recurso: artículo
Fecha de publicación:2019
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/13758
Acceso en línea:https://hdl.handle.net/20.500.14352/13758
Access Level:acceso abierto
Palabra clave:52
Digital cameras
Color
Sensitivity
Smartphones
Methodology
Vegetation
Aerosols
Física atmosférica
2501 Ciencias de la Atmósfera
Descripción
Sumario: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.