<title>Sensor- and detection-algorithm-based clutter metrics</title>

Abstract

Clutter metrics are important image measures for evaluating the expected performance of sensors and detection algorithms. Typically, clutter metrics attempt to measure the degree to which background objects resemble targets. That is, the more target-like objects or attributes in the background the higher the clutter level. However, it is critically important that the characteristics of the sensor systems and the detection algorithms be included in any measure of clutter. For example, clutter to a coarse resolution sensor coupled with a pulse thresholding detection algorithm is not necessarily clutter to a second generation FLIR with a man in the loop. Using present state- of-the-art first and second order clutter metrics and respective performance studies, a new class of sensor/algorithm clutter metrics will be derived which explicitly use characteristics of the sensor and detection algorithms. A methodology will be presented for deriving sensor/algorithm dependent clutter metric coefficients and algorithms for a broad class of systems.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.