Advances in Target Acquisition Modeling II

Thomas J. Meitzler; Alexander Toet

doi:10.1117/1.1410760

1 September 2001 Advances in Target Acquisition Modeling II

Thomas J. Meitzler, Alexander Toet

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Optical Engineering, Vol. 40, Issue 9, (September 2001). https://doi.org/10.1117/1.1410760

The problem of modeling electro-optical (EO) systems for the purpose of ground vehicle countermeasure development and system performance evaluation has been around for many years. This special section is devoted to recent advances in (1) computational techniques and testing procedures to predict the detectability of man-made objects in the field and in (2) methods to validate and calibrate these techniques and procedures. Most metrics that are currently used to quantify visual target distinctness and to predict the probability of detection of a target in clutter do not relate to properties of the human visual system. As a result, their predictions do not correlate with the results of human observer tests. A well-known example is the mean square error (MSE) in intensity. Although this metric has a good physical and theoretical basis, it correlates poorly with observer performance. This is due to the fact that the human visual system does not analyze an image in a simple point-by-point manner. Bottom-up grouping mechanisms appear to drive the formation of emergent perceptual units from preattentively extracted stimulus features (e.g., edges or texture elements). When searching for known targets, top-down priming signals may influence the organization of search regions. Salient areas may then be selected for further inspection.

©(2001) Society of Photo-Optical Instrumentation Engineers (SPIE)

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Thomas J. Meitzler and Alexander Toet "Advances in Target Acquisition Modeling II," Optical Engineering 40(9), (1 September 2001). https://doi.org/10.1117/1.1410760

Published: 1 September 2001

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