A Fast New Small Target Detection Algorithm Based on Regularizing Partial Differential Equation in IR Clutter

  • Authors:

  • Biyin Zhang;Tianxu Zhang;Kun Zhang

  • Affiliations:

  • Institute for Pattern Recognition and Artificial Intelligence, State Key Laboratory for Multispectral Information Processing technology, Huazhong University of Science and Technology, Wuhan, 43007 ...;Institute for Pattern Recognition and Artificial Intelligence, State Key Laboratory for Multispectral Information Processing technology, Huazhong University of Science and Technology, Wuhan, 43007 ...;Institute for Pattern Recognition and Artificial Intelligence, State Key Laboratory for Multispectral Information Processing technology, Huazhong University of Science and Technology, Wuhan, 43007 ...

  • Venue:
  • ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
  • Year:
  • 2007

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Abstract

To detect and track moving dim targets against the complex cluttered background in infrared (IR) image sequences is still a difficult issue because the nonstationary structured background clutter usually results in low target detectability and high probability of false alarm. A brand-new adaptive Regularizing Anisotropic Filter based on Partial Differential Equation (RAFPDE) is proposed to detect and track a small target in such strong cluttered background. A regularization operator is employed to adaptively eliminate structured background and simultaneously enhance target signal. The proposed algorithm's performance is illustrated and compared with a two-dimensional least mean square adaptive filter algorithm and a BP neural network prediction algorithm on real IR image data. Experimental results demonstrate that the proposed novel method is fast and effective.