A three stage approach to large target acquisition in spectral images

Research output: Contribution to journalConference articlepeer-review

Abstract

Over the last few years, we have developed an algorithm which detects anomalous targets in hyperspectral or multispectral images. The algorithm takes a data (image) cube with a completely unknown background, segments the cube, assigns the largest clusters as background, and determines which pixels are anomalous to the background. In the work to be presented here, we will add two additional modules. First, since our present mission is to detect military targets in a fairly barren rural background, we use the SAVI (or NDVI) metric to detect items which appear to contain chlorophyll. In this way, we can eliminate objects which in retrospect were the right sizes and shapes but were in reality plants. Second, we have developed CFAR methods to achieve a Constant False Alarm Rate while giving us the maximum probability of detecting the targets. Actual data will be analyzed by the algorithm; the ability to both determine if a target is present and where its location is will be shown.

Original languageEnglish
Article number59870U
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5987
DOIs
StatePublished - 1 Dec 2005
EventElectro-Optical and Infrared Systems: Technology and Applications II - Bruges, Belgium
Duration: 26 Sep 200527 Sep 2005

Keywords

  • Anomaly Detection
  • CFAR
  • Hyperspectral Data
  • Multispectral Data
  • NDVI
  • SAVI
  • SRC

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