Nonuniformity correction and correctability of infrared focal plane arrays

Schulz, M.; Caldwell, L.

doi:10.1016/1350-4495(94)00002-3

Cited by 153 publications

(89 citation statements)

References 4 publications

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“…Some disadvantage of this NUC method is high complexity of a correction formula at higher order polynomials. For in− stance, the formula defining detector response value after correction at the second−order approximating polynomial is given by [7] . (5) In Ref.…”

Section: Nuc Methodsmentioning

confidence: 99%

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Test and evaluation of reference-based nonuniformity correction methods for microbolometer infrared detectors

Orżanowski

Madura

2010

Opto-Electronics Review

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In the paper, reference-based nonuniformity correction methods for microbolometer infrared detectors are discussed and tested. In order to evaluate their effectiveness, a complete readout circuit for amorphous silicon microbolometer focal plane array has been designed. The tests were carried out on a developed stand including several extended blackbodies. Some modification of standard two-point correction algorithm incorporating detectors response at external shutter to compensate offset drift is also proposed. The obtained results are presented.

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Section: Nuc Methodsmentioning

confidence: 99%

“…In Ref. 7, the authors propose a NUC algorithm where the response deviation DY ij (f) of the detector ij from the mean response Y ( ) f of all detectors in array to the same in− frared radiance flux f is approximated by the n−order poly− nomial of Y ( ) f . The approximating polynomial is defined as follows…”

Section: Nuc Methodsmentioning

confidence: 99%

Test and evaluation of reference-based nonuniformity correction methods for microbolometer infrared detectors

Orżanowski

Madura

2010

Opto-Electronics Review

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“…The function U mn (ϑ O ) of the pixel at location (m, n) is not linear. Therefore, the characteristic curve is generally described with a secondorder polynomial (Schulz and Caldwell, 1995). For radiometric IR cameras this regression is not sufficient.…”

Section: Non-uniformity Correctionmentioning

confidence: 99%

“…The characteristic curve corrections described in the literature Caldwell, 1995, andWallrabe, 2001) also refer to photon sensors, whose function U mn ( O ) is often not linear, as well as IR vision equipment without radiometric adjustment. In contrast, the relationship between the radiant flux and the pixel voltage U mn of a microbolometer is linear and can be used for describing a characteris- Figure 6.…”

Section: Non-uniformity Correctionmentioning

confidence: 99%

Calibration of uncooled thermal infrared cameras

Budzier

Gerlach

2015

J. Sens. Sens. Syst.

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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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“…The PRNU is due to the difference of response of each pixel to a given signal; it is therefore a signal-dependent noise. These two types of non-uniformities have been corrected by the characterization of the CCD in use [12][13][14][15]. The FPN characterization is made by obscuring the CCD and capturing the dark image.…”

Section: Correction At Low Spatial Frequenciesmentioning

confidence: 99%

Improvements for determining the modulation transfer function of charge-coupled devices by the speckle method

Pozo¹,

Ferrero²,

Rubiño³

et al. 2006

Opt. Express

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We present and evaluate two corrections applicable in determining the modulation transfer function (MTF) of a charge-coupled device (CCD) by the speckle method that minimize its uncertainty: one for the low frequency region and another for the high frequency region. The correction at the low-spatial-frequency region enables attenuation of the high power-spectral-density values that arise from the field and CCD response non-uniformities. In the high-spatial-frequency region the results show that the distance between the CCD and the aperture is critical and significantly influences the MTF; a variation of 1 mm in the distance can cause a root-mean-square error in the MTF higher than 10%. We propose a simple correction that minimizes the experimental error committed in positioning the CCD and that diminishes the error to 0.43%.

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Nonuniformity correction and correctability of infrared focal plane arrays

Cited by 153 publications

References 4 publications

Test and evaluation of reference-based nonuniformity correction methods for microbolometer infrared detectors

Test and evaluation of reference-based nonuniformity correction methods for microbolometer infrared detectors

Calibration of uncooled thermal infrared cameras

Improvements for determining the modulation transfer function of charge-coupled devices by the speckle method

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