Published: June 14, 2018
Novel Performance Evaluation of Thermal Camera Based on VOx Bolometer Focal Plane Array via Analysis of Sigma NETD, Mean NETD, and Roughness Index [PDF]
Cheng-De Lee, Shiang-Feng Tang, and Tzu -Chiang Chen
(Received January 22, 2018; Accepted April 2, 2018)
Keywords: roughness index (RI), noise equivalent temperature difference (NETD), full width at half maximum (FWHM), non-uniformity correction (NUC)
With recent advancements in thermal imaging, the evaluation of thermal imaging performance has become important. In this study, the thermal-camera performance parameters of roughness index (RI), noise equivalent temperature difference (NETD), and the full width at half maximum (FWHM) of a statistical NETD histogram are investigated and compared by varying the integration times at different operating temperatures for vanadium oxide (VOx)-based microbolometer focal plane arrays (FPAs) with the use of the Matlab algorithm platform. The quantitative performance assessment of an uncooled VOx microbolometer-based thermal imager, which was designed and fabricated by researchers from the National Chung-Shan Institute Science of Technology (NCSIST), Taiwan, and the National Optics Institute (INO), Canada, is proposed systematically. Explicitly, the uncompressed video data streams before non-uniformity correction (NUC) using two-point temperature calibration were acquired for integration times of 16.67, 33.33, and 50 ms at three operating temperatures of 10, 15, and 20 °C. The results from the estimations of NETD, FWHM of the NETD histogram, and the RI for the thermal imager are discussed for the imaging performance evaluation in different infrared operation scenarios. We believe that our findings can significantly contribute to the further development of IR imaging technology.
Corresponding author: Shiang-Feng Tang
Cite this article
Cheng-De Lee, Shiang-Feng Tang, and Tzu -Chiang Chen, Novel Performance Evaluation of Thermal Camera Based on VOx Bolometer Focal Plane Array via Analysis of Sigma NETD, Mean NETD, and Roughness Index, Sens. Mater., Vol. 30, No. 6, 2018, p. 1283-1296.