Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Chinese Optics Letters
  • Vol. 3,
  • Issue 6,
  • pp. 322-325
  • (2005)

Track before detect for point targets with particle filter in infrared image sequences

Not Accessible

Your library or personal account may give you access

Abstract

The problem of detecting and tracking point targets in a sequence of infrared images with very low signal-to-noise ratio (SNR) is investigated in this paper. A track before detect algorithm for infrared (IR) point target is developed based on particle filter. The particle filter is used to estimate the state of the target in track stage. The unnormalized weights of the output of the filter are used to approximately construct the likelihood ratio for hypothesis test in detection stage. Experiment results with the real image sequences that SNR is about 2.0 show that the proposed algorithm can successfully detect and track point target.

© 2005 Chinese Optics Letters

PDF Article
More Like This
Parametric temporal compression of infrared imagery sequences containing a slow-moving point target

Revital Huber-Shalem, Ofer Hadar, Stanley R. Rotman, and Merav Huber-Lerner
Appl. Opt. 55(5) 1151-1163 (2016)

Optimal target tracking on image sequences with a deterministic background

François Goudail and Philippe Réfrégier
J. Opt. Soc. Am. A 14(12) 3197-3207 (1997)

Compression of infrared imagery sequences containing a slow-moving point target

Revital Huber-Shalem, Ofer Hadar, Stanley R. Rotman, and Merav Huber-Lerner
Appl. Opt. 49(19) 3798-3813 (2010)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.