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Institute of Electrical and Electronic Engineers (IEEE)

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IEEE Sensors Journal

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Mid-wave and long-wave infrared (IR) quantum-dots-in-a-well (DWELL) focal plane arrays (FPAs) are promising technology for multispectral (MS) imaging and sensing. The DWELL structure design provides the detector with a unique property that allows the spectral response of the detector to be continuously, albeit coarsely, tuned with the applied bias. In this paper, a MS classification capability of the DWELL FPA is demonstrated. The approach is based upon: 1) imaging an object repeatedly using a sequence of bias voltages in the tuning range of the FPA and then 2) applying a classification algorithm to the totality of readouts, over multiple biases, at each pixel to identify the “class” of the material. The approach is validated for two classification problems: separation among different combinations of three IR filters and discrimination between rocks. This work is the first demonstration of the MS classification capability of the DWELL FPA.


Accepted version. IEEE Sensors Journal, Vol. 11, No. 6 (June 2011): 1342-1351. DOI. © 2011 Institute of Electrical and Electronic Engineers (IEEE). Used with permission.

Majeed M. Hayat was affiliated with University of New Mexico, Albuquerque at the time of publication.

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