Multi-frame linear regressive filter for the measurement of infrared pixel spatial response and MTF from sparse data

A challenging point in the prediction of the image quality of infrared imaging systems is the evaluation of the detector modulation transfer function (MTF). In this paper, we present a linear method to get a 2D continuous MTF from sparse spectral data. Within the method, an object with a predictable...

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Veröffentlicht in:	Optics express 2018-03, Vol.26 (5), p.5200-5211
Hauptverfasser:	Huard, Edouard, Derelle, Sophie, Jaeck, Julien, Nghiem, Jean, Haïdar, Riad, Primot, Jérôme
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Sprache:	eng
Schlagworte:	Engineering Sciences Optics Photonic Signal and Image processing
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container_issue	5
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container_title	Optics express
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creator	Huard, Edouard Derelle, Sophie Jaeck, Julien Nghiem, Jean Haïdar, Riad Primot, Jérôme
description	A challenging point in the prediction of the image quality of infrared imaging systems is the evaluation of the detector modulation transfer function (MTF). In this paper, we present a linear method to get a 2D continuous MTF from sparse spectral data. Within the method, an object with a predictable sparse spatial spectrum is imaged by the focal plane array. The sparse data is then treated to return the 2D continuous MTF with the hypothesis that all the pixels have an identical spatial response. The linearity of the treatment is a key point to estimate directly the error bars of the resulting detector MTF. The test bench will be presented along with measurement tests on a 25 μm pitch InGaAs detector.
doi_str_mv	10.1364/OE.26.005200
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subjects	Engineering Sciences Optics Photonic Signal and Image processing
title	Multi-frame linear regressive filter for the measurement of infrared pixel spatial response and MTF from sparse data
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