Modeling transient thermal behavior of shutter-less microbolometer-based infrared cameras

Tempelhahn, A.; Budzier, Helmut; Krause, Volker; Gerlach, Gerald

doi:10.1117/12.2066624

Cited by 3 publications

(4 citation statements)

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“…During the calibration procedure the correction coefficients are determined which consider the temperature-dependent sensor parameters and estimates of the disturbing camera radiation using additional temperature probes placed inside the camera housing. This method combines experiences of our previous works on calibration of infrared cameras with shutters [3] and shutter-less infrared cameras using temperature-stabilized microbolometer FPAs [5]. Figure 1.…”

Section: Radiation Modelmentioning

confidence: 97%

“…The individual steady-state regressions are combined to a more complex regression model which allows to estimate the behavior during transient thermal conditions. Additional information about the temperature distribution inside the camera is provided by the time derivatives of the camera temperatures and cross-correlation coefficients formed by multiplying two or more camera temperature inputs [5]. The final regression model is composed of the following three groups of inputs: (i) absolute temperatures, (ii) time derivatives and (iii) cross-correlation of temperature inputs .…”

Section: Offset Voltage Correctionmentioning

confidence: 99%

“…With the use of a heating chamber the ambient temperature is controlled and correction parameters based on the sensor temperature are determined. In [5] a shutter-less offset correction for temperature stabilized infrared cameras has been described. The disturbing radiation is estimated using additional temperature probes inside the camera housing.…”

Section: Introductionmentioning

confidence: 99%

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Improving the shutter-less compensation method for TEC-less microbolometer-based infrared cameras

et al. 2015

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Shutter-less infrared cameras based on microbolometer focal plane arrays (FPAs) are the most widely used cameras in thermography, in particular in the fields of handheld devices and small distributed sensors. For acceptable measurement uncertainty values the disturbing influences of changing thermal ambient conditions have to be treated corresponding to temperature measurements of the thermal conditions inside the camera. We propose a compensation approach based on calibration measurements where changing external conditions are simulated and all correction parameters are determined. This allows to process the raw infrared data and to consider all disturbing influences. The effects on the pixel responsivity and offset voltage are considered separately. The responsivity correction requires two different, alternating radiation sources. This paper presents the details of the compensation procedure and discusses relevant aspects to gain low temperature measurement uncertainty.

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Section: Radiation Modelmentioning

confidence: 97%

Section: Offset Voltage Correctionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Improving the shutter-less compensation method for TEC-less microbolometer-based infrared cameras

et al. 2015

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“…During this reference time the sensor is blinded and additionally the shutter action can be a source of acoustic noise. For these reasons shutterless operation of micro-bolometer cameras is highly desirable [1][2][3] . Unfortunately, the sensor response is not uniquely a function of the detector temperature; but also the ambient or the camera casing temperature is an important factor.…”

Section: Introductionmentioning

confidence: 99%

Implementation and performance of shutterless uncooled micro-bolometer cameras

et al. 2015

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A shutterless algorithm is implemented into the Xenics LWIR thermal cameras and modules. Based on a calibration set and a global temperature coefficient the optimal non-uniformity correction is calculated onboard of the camera. The limited resources in the camera require a compact algorithm, hence the efficiency of the coding is important. The performance of the shutterless algorithm is studied by a comparison of the residual non-uniformity (RNU) and signal-tonoise ratio (SNR) between the shutterless and shuttered correction algorithm. From this comparison we conclude that the shutterless correction is only slightly less performant compared to the standard shuttered algorithm, making this algorithm very interesting for thermal infrared applications where small weight and size, and continuous operation are important.

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