Target identification performance as a function of low spatial frequency image content

Abstract

Current imaging system performance models use either the minimum resolvable temperature difference or the minimum resolvable contrast concepts to predict target identification performance. Both of these performance functions describe the limiting frequency that can be viewed through the imaging system at a particular contrast. No credit is given to the system for the amount of low frequency (lower than the limiting frequency) information that is passed through the system. We determine whether the low spatial frequency information is important in the target identification task. Previous experiments show that no degradation is seen on character recognition if a high-pass, edge enhancing filter is applied to character images. This is not the case in target identification performance, where the targets of interest are military tanks. A number of filters (six levels of blur at four bandwidth configurations) are applied to tank imagery including high-pass filters to reduce the low frequency image content. A perception experiment is performed to determine whether target identification performance was degraded with a reduced amount of low spatial frequency image content. The probability of target identification is calculated from the observer responses and the identification performance is evaluated as a function of low spatial frequency image content. Low frequency information is shown to contribute to the overall system performance.