Institute of Electrical and Electronic Engineers (IEEE)
IEEE Sensors Journal
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.
Paskaleva, Biliana S.; Jang, Woo-Yong; Sharma, Yagya D.; Krishna, Sanjay; and Hayat, Majeed M., "Multispectral Classification With Bias-Tunable Quantum Dots-in-a-Well Focal Plane Arrays" (2011). Electrical and Computer Engineering Faculty Research and Publications. 543.
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