Alan Camp EOIR Technologies (United States) Steven K. Moyer U.S. Army Night Vision & Electronic Sensors Directorate (United States) Richard K. Moore U.S. Army Redstone Technical Test Ctr. (United States)
Prior work has shown that the masked target transform volume (MTTV) clutter metric provides a measure of scene clutter that better correlates to measured probability of detection for human observers than several previously published clutter metrics. Several factors involved in using the MTTV to assess clutter in imagery are discussed here. A previously published modification to the MTTV metric to provide a normalized output value comparable across different image sets regardless of scene size is reviewed. Initial MTTV development required knowledge of a scene's target signature and produced an unbounded metric value. Metric behavior is discussed for the case in which an average of several target signatures is used in place of a specific target signature. This allows the MTTV to be calculated for images that do not contain a target. It is shown that the user may trade computational efficiency with metric accuracy to suit a particular application. The sensitivity of the metric to variations in image noise level, target segmentation error, and viewing distance are also presented.