A Matrix Spatial and Temporal Matched Filter for Background Suppression.

Abstract

The maximum likelihood method is applied to the problem of extracting the correct sequence of spatial patterns from the corresponding sequence of measurement frames corrupted by background noise. Each measurement frame is modeled as the sum of a pattern matrix and a background noise matrix. The model proposed for the statistics of the sequence of background matrices results in jointly Gaussian elements whose correlations are product separable in row, column, and frame indices. The logarithm of the likelihood function is computed and involves a matched filtering operation on the measurement frames, which acts to suppress the background relative to the pattern. Because of the product separability in the background element correlations, this matched filtering operation is accomplished by pre- and post-multiplying the measurement frames by the inverses of the background row and column correlation matrices, respectively. Thus, the measurement frames are operated on in their original matrix format without resorting to stacking. Applications include the detection of targets in background noise. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Apr 25, 1979
Accession Number
ADA071136

Entities

People

  • S. M. Melzer

Organizations

  • The Aerospace Corporation

Tags

Communities of Interest

  • Sensors
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Background Noise
  • Data Science
  • Detection
  • Detectors
  • Digital Image Processing
  • Digital Images
  • False Alarms
  • Image Processing
  • Information Processing
  • Measurement
  • Noise
  • Probability
  • Security
  • Sequences
  • Statistics
  • Two Dimensional
  • Warning Systems

Readers

  • Image Processing and Computer Vision.
  • Operations Research