MACHINE VISION BASED IR IMAGING SYSTEM DETECTION PERFORMANCE EVALUATION

[in Chinese]; [in Chinese]

Journals >Journal of Infrared and Millimeter Waves >Volume 22 >Issue 4 >Page 273 > Article

Journal of Infrared and Millimeter Waves
Vol. 22, Issue 4, 273 (2003)

MACHINE VISION BASED IR IMAGING SYSTEM DETECTION PERFORMANCE EVALUATION

[in Chinese]^1、2 and [in Chinese]¹

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¹[in Chinese]

²[in Chinese]

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DOI: Cite this Article

[in Chinese], [in Chinese]. MACHINE VISION BASED IR IMAGING SYSTEM DETECTION PERFORMANCE EVALUATION[J]. Journal of Infrared and Millimeter Waves, 2003, 22(4): 273 Copy Citation Text

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References

[1] Chtister Wigren. A generic IRST detection performance model. SPIE Proceedings, 2000, 4030: 206-217

[2] John D McGlynn, Dino J Sofianos. Parametric Model-based characterization of IR clutter. SPIE Proceedings, 1995, 2470: 236-244

[3] Agostino J D, Webb C, 3-D analysis framework and measurement methodology for imaging system noise. SPIE Proceedings, 1991, 1488: 110-121

[4] Thomas J Meizler, Haprpreet Singh, Labib Arefeh, et al. Computing the probability of target detection in infrared and visual scenes using the fuzzy logic approach. SPIE Proceedings, 1997, 3063: 2-11

[5] HUANG Shi-Ke, LI Li-Juan, CHEN Bao-Guo, et al. Performance evaluation system of signal processing algorithm. SPIE Proceedings, 2001, 4553: 185-190

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[in Chinese], [in Chinese]. MACHINE VISION BASED IR IMAGING SYSTEM DETECTION PERFORMANCE EVALUATION[J]. Journal of Infrared and Millimeter Waves, 2003, 22(4): 273

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