Gabor Jets for Clutter Rejection in Infrared Imagery

Abstract

The performance of an infrared imagery based (IR) automatic target detection algorithm suffers from several variables. The target size, shape, orientation and brightness play a role, as well as the cluttered backgrounds [1-5], which often exhibit greater intensity than the sensor noise or intensity of the targets to be detected. Once the detection process is finished and further decisions pending in the ATR system, one would like a simple technique to further reduce false alarms. The problem again, is one of recognition and past research has shown that joint spatial-frequency representations using Gabor schemes is beneficial in many automated, computer vision applications. We will present results using Gabor Jets together with a back propagation neural network for a detector post processing procedure, which could substantially reduce false alarms.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2004
Accession Number
ADA487612

Entities

People

  • Mark Wellman
  • Nasser M. Nasrabadi

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence Software
  • Computer Vision
  • Computing System Architectures
  • Data Sets
  • Databases
  • Detection
  • Detectors
  • Extraction
  • False Alarms
  • Feature Extraction
  • Machine Learning
  • Neural Networks
  • Orientation (Direction)
  • Rejection
  • Warning Systems

Readers

  • Image Processing and Computer Vision.
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • AI & ML