An advanced radiometric calibration approach for uncooled thermal cameras

Abstract

Uncooled thermal cameras are increasingly used in thermography applications due to their lower cost and size. However, there are two significant limiting constraints which must be taken into consideration in a radiometric calibration before the actual application: (i) temporal non‐uniformity (a temperature‐dependent drift problem); and (ii) spatial non‐uniformity (fixed‐pattern noise – FPN). Conventional temporal non‐uniformity corrections (NUC) take advantage of an internal reference source but such methods are not valid for sequential images when the focal‐plane array (FPA) temperature is changing rapidly. A novel shutterless correction method is proposed to stabilise the camera's response. Moreover, instead of implementing the spatial NUC first, multi‐point correction is leveraged to remove FPN after the temporal NUC. Finally, a Planck curve is applied to convert thermal image values into object temperatures. Experimental results show that the proposed method is more effective for images with rapidly changing FPA temperatures than conventional shutterless methods and traditional shutter‐based methods.

A Review of Current and Potential Applications of Remote Sensing to Study the Water Status of Horticultural Crops

“…Thus, the thermal image can be unreliable especially when the internal temperature of the camera is changing rapidly, such as during camera warmup period or during the flight when a gust of cool wind results in cooling of the camera. To overcome this challenge, the user may need to provide sufficient startup time before operation (preferably 30-60 min) [102,[143][144][145], shield the camera to minimize the change in the internal temperature of the camera [142], calibrate the camera [146][147][148][149][150][151][152][153], and perform frequent flat-field corrections.…”

Supervised Detection of Façade Openings in 3D Point Clouds with Thermal Attributes

“…For the radiometric calibration of the first thermal image sequence, we used the commercial software FLIR GEV (version 1.7), which uses a conventional shutter-based method. The second set of thermal images was processed by the algorithms for radiometric calibration presented in Lin et al (2017) [22], which represent a shutter-less method. It must be noticed that exact kinetic temperatures, which refer to the internal or true temperature, are unknown as long as the material type and the corresponding emissivity of the object are unknown.…”

“…Such differences between data sets are most likely related to the different method of thermal information extraction during data acquisition. The 3D point cloud of façade 1 was attributed to TIR data calibrated with commercial software, while the second set of thermal images was processed by our own algorithm [22]. The latter workflow of data processing proves itself to be more suitable for the classification purpose, due to the better accuracy of the finally obtained thermal information and its higher consistency within the whole data set (also visible by comparing Figure 2a,b).…”

Evaluating Image Tracking Approaches for Surface Velocimetry With Thermal Tracers

“…However, for uncooled thermal cameras, which suffer from heavy nonuniformity problems such as vignetting effect, radiometric calibration is more efficient. In this study, a shutterless radiometric calibration approach, which only needs calibration once, is used to improve image quality and measurement accuracy (Lin, Maas, et al, ). It is in contrast to the two‐point blackbody calibration method, which needs to be calibrated periodically (Chickadel et al, ).…”