Zero-mean minace filters for detection in visible EO imagery

We consider using minimum noise and correlation energy (Minace) filters to detect objects in high-resolution ElectroOptical (EO) visible imagery. EO data is a difficult detection problem because only primitive features such as edges and corners are useful. This occurs because the targets and the background in EO data can have very similar gray levels, which leads to very low contrast targets; no hot spots (present in infrared (IR) data) or bright reflectors (present in synthetic aperture radar (SAR) data) exist in EO data. Since only geometrical (aspect view) distortions are expected in EO data (no thermal variations, as in IR, are expected), we consider using distortion-invariant Minace filters to detect targets. Such filters are shift-invariant and have been shown to be suitable for detection in other data (IR and SAR). Minace filters are attractive distortion-invariant filters (DIFs) because they require only a few filters to handle detection of multiple target classes. These filters must be modified for use on EO data. For EO data, zero-mean Minace filters formed from zero-mean, unit-energy data are used, and thus use of local zero-mean normalized correlations are needed. They show excellent initial detection results.