Abstract. The calibration of uncooled thermal infrared (IR) cameras to absolute temperature measurement is a time-consuming, complicated process that significantly influences the cost of an IR camera. Temperaturemeasuring IR cameras display a temperature value for each pixel in the thermal image. Calibration is used to calculate a temperature-proportional output signal (IR or thermal image) from the measurement signal (raw image) taking into account all technical and physical properties of the IR camera. The paper will discuss the mathematical and physical principles of calibration, which are based on radiometric camera models. The individual stages of calibration will be presented. After start-up of the IR camera, the non-uniformity of the pixels is first corrected. This is done with a simple two-point correction. If the microbolometer array is not temperature-stabilized, then, in the next step the temperature dependence of the sensor parameters must be corrected. Ambient temperature changes are compensated for by the shutter correction. The final stage involves radiometric calibration, which establishes the relationship between pixel signal and target object temperature. Not all pixels of a microbolometer array are functional. There are also a number of defective, so-called "dead" pixels. The discovery of defective pixels is a multistep process that is carried out after each stage of the calibration process.

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Abstract. Infrared (IR) cameras based on microbolometer focal plane arrays (FPAs) are the most widely used cameras in thermography. New fields of applications like handheld devices and small distributed sensors benefit from the latest sensor improvements in terms of cost and size reduction. In order to compensate for disturbing influences derived from changing ambient conditions, radiometric cameras use an optical shutter for online recalibration purposes, partially also together with sensor temperature stabilization. For these new applications, IR cameras should consist only of infrared optics, a sensor array, and digital signal processing (DSP). For acceptable measurement uncertainty values without using an optical shutter (shutter-less), the disturbing influences of changing thermal conditions have to be treated based on temperature measurements of the camera interior. We propose a compensation approach based on calibration measurements under controlled ambient conditions. All correction parameters are determined during the calibration process. Without sensor temperature stabilization (TEC-less), the pixel responsivity is also affected by the camera temperature changes and has to be considered separately. This paper presents the details of the compensation procedure and discusses relevant aspects to gain low temperature measurement uncertainty. The residual measurement uncertainty values are compared to the shutter-based compensation approach.

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.

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