Accession Number:

ADA446551

Title:

Improving Background Multivariate Normality and Target Detection Performance Using Spatial and Spectral Segmentation

Descriptive Note:

Major rept.

Corporate Author:

ROCHESTER INST OF TECH NY CHESTER F CARLSON CENTER FOR IMAGING SCIENCE

Report Date:

2006-04-28

Pagination or Media Count:

6.0

Abstract:

Target deteetion in reflective hyperspeetral imagery generally involves the application of a spectral matched filter on a per-pixei basis to create an image of the target lihenhood of occupying each pixel. Stochastic or unstructured target detection tcehniques require the user to define an estimate of the background mean and covariance from which to separate out the desired targets in the image. Typically, scene-wide statistics are used, although it Is simple to show that this methodology does not produce sufficiently multivariate normal bachgrounds nor does it necessarily represent the best suppression of likely false alarms.

Subject Categories:

  • Target Direction, Range and Position Finding

Distribution Statement:

APPROVED FOR PUBLIC RELEASE