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Small Target Detection Improvement in Hyperspectral Image

  • Tao Lin
  • Julien Marot
  • Salah Bourennane
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8192)

Abstract

Target detection is an important issue in the HyperSpectral Image (HSI) processing field. However, current spectral-identification-based target detection algorithms are sensitive to the noise and most denoising algorithms cannot preserve small targets, therefore it is necessary to design a robust detection algorithm that can preserve small targets. This paper utilizes the recently proposed multidimensional wavelet packet transform with multiway Wiener filter (MWPT-MWF) to improve the target detection efficiency of HSI with small targets in the noise environment. The performances of the our method are exemplified using simulated and real-world HSI.

Keywords

Hyperspectral image small target detection multiway Wiener Filter 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Tao Lin
    • 1
  • Julien Marot
    • 1
  • Salah Bourennane
    • 1
  1. 1.Institut Fresnel / CNRS-UMR 7249Ecole Centrale Marseille, Aix-Marseille UniversitéMarseilleFrance

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