Optimal Correlation Filters for Detecting a Target in Background Noise.

Abstract

This report focuses on the development of optimal correlation filters for pattern recognition with spatially disjoint target and scene noise. In particular, it is shown that, for this class of problems, the matched filter expressions and optimum receivers derived under the overlapping input signal and scene noise assumption may not perform well in the presence of spatially disjoint input signal and scene noise.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1996
Accession Number
ADA312023

Entities

People

  • Bahram Javidi

Organizations

  • University of Connecticut

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Background Noise
  • Computer Simulations
  • Cross Correlation
  • Data Science
  • Delta Functions
  • Detection
  • Detectors
  • Filters
  • Gaussian Noise
  • Information Science
  • Matched Filters
  • Noise
  • Pattern Recognition
  • Probability
  • Probability Density Functions
  • Recognition
  • Signal Processing

Fields of Study

  • Engineering

Readers

  • Image Processing and Computer Vision.
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms