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Proceedings Paper

Modeling the effects of contrast enhancement on target acquisition performance
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Paper Abstract

Contrast enhancement and dynamic range compression are currently being used to improve the performance of infrared imagers by increasing the contrast between the target and the scene content, by better utilizing the available gray levels either globally or locally. This paper assesses the range-performance effects of various contrast enhancement algorithms for target identification with well contrasted vehicles. Human perception experiments were performed to determine field performance using contrast enhancement on the U.S. Army RDECOM CERDEC NVESD standard military eight target set using an un-cooled LWIR camera. The experiments compare the identification performance of observers viewing linearly scaled images and various contrast enhancement processed images. Contrast enhancement is modeled in the US Army thermal target acquisition model (NVThermIP) by changing the scene contrast temperature. The model predicts improved performance based on any improved target contrast, regardless of feature saturation or enhancement. To account for the equivalent blur associated with each contrast enhancement algorithm, an additional effective MTF was calculated and added to the model. The measured results are compared with the predicted performance based on the target task difficulty metric used in NVThermIP.

Paper Details

Date Published: 11 April 2008
PDF: 10 pages
Proc. SPIE 6941, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XIX, 69410K (11 April 2008); doi: 10.1117/12.785558
Show Author Affiliations
Todd W. Du Bosq, U.S. Army RDECOM CERDEC NVESD (United States)
Jonathan D. Fanning, U.S. Army RDECOM CERDEC NVESD (United States)


Published in SPIE Proceedings Vol. 6941:
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XIX
Gerald C. Holst, Editor(s)

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