Radiometric and spectral comparison of inexpensive camera systems used for remote sensing

Standardized spectral and radiometric calibration of consumer cameras

“…10 agree well with those found in the literature [1,2,13,19,23,24,46,51,54,57,[59][60][61][62], with the RGB curves centered around 600, 520, and 470 nm, respectively. Notably, the strong secondary peaks seen in [2,51] were not found in our data and may be JPEG artefacts. Differences are mainly found in the wings, such as the NIR cut-offs [19,46] and harmonics.…”

“…While this correction is sometimes considered a major advantage of JPEG data over RAW data, the internal model of the iPhone SE was shown to be significantly less accurate (RMSE = 5.9%) than one based on our data (RMSE = 0.5%), contradicting this notion. Moreover, residual vignetting effects up to 15% have been observed in JPEG data [51]. A comparison to the internal correction data in Android smartphones, consisting of pixel-by-pixel look-up tables, has not yet been done since these data are relatively difficult to access.…”

“…Moreover, certain calibrations are device-dependent and would need to be done separately on each device. Spectral and radiometric calibrations of seven cameras, including the Raspberry Pi, are given in [51]. These calibrations include dark current, flat-fielding, linearity, and spectral characterization.…”

“…However, for the five digicams included in this work, JPEG data were used, severely limiting the quality and usefulness of these calibrations, as described above.Spectral characterizations are more commonly published since these are vital for quantitative color analysis. Using various methods, the spectral responses of several Canon [1,19,23,24,46,51,54,61], Nikon [1,13,23,24,54,[59][60][61][62], Olympus [23, 24, 51], Panasonic [46], SeaLife [13], Sigma [60], and Sony [1, 23, 46, 51, 61] digital cameras (digicams), as well as a number of smartphones [2, 23], have been measured. Direct comparisons between >2 different camera models are given in [1,2,23,46,51].…”

Development of a Simplified Radiometric Calibration Framework for Water-Based and Rapid Deployment Unmanned Aerial System (UAS) Operations

“…Flight altitudes of small UAS (sUAS) typically do not exceed 250 meters due to governmental restrictions on UAS operations [34]. As a result, numerous UAS studies have implemented an empirical line method (ELM) for radiometric calibration of UAS imagery [35,36,[45][46][47][37][38][39][40][41][42][43][44]. The foundation of an ELM is the regression of ground-based spectroradiometer measurements and airborne remotely sensed measurements of a spectrally stable calibration target to develop calibration equations that convert image digital numbers (DNs) to physical at-surface reflectance units [48].…”