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Morphological Neural Networks of Background Clutter Adaptive Prediction for Detection of Small Targets in Image Data

  • Honggang Wu
  • Xiaofeng Li
  • Zaiming Li
  • Yuebin Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)

Abstract

An effective morphological neural network of background clutter prediction for detecting small targets in image data is proposed in this paper. The target of interest is assumed to have a very small spatial spread, and is obscured by heavy background clutter. The clutter is predicted exactly by morphological neural networks and subtracted from the input signal, leaving components of the target signal in the residual noise. Computer simulations of real infrared data show better performance compared with other traditional methods.

Keywords

Small Target Background Clutter Residual Noise Morphological Filter Closing Operation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Honggang Wu
    • 1
  • Xiaofeng Li
    • 1
  • Zaiming Li
    • 1
  • Yuebin Chen
    • 1
  1. 1.School of Communication and Information EngineeringUniversity of Electronics Science and Technology of ChinaChengduChina

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