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.
The original version of this chapter was revised: The copyright line was incorrect. This has been corrected. The Erratum to this chapter is available at DOI: 10.1007/978-3-319-02895-8_64
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Lin, T., Marot, J., Bourennane, S. (2013). Small Target Detection Improvement in Hyperspectral Image. In: Blanc-Talon, J., Kasinski, A., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2013. Lecture Notes in Computer Science, vol 8192. Springer, Cham. https://doi.org/10.1007/978-3-319-02895-8_41
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DOI: https://doi.org/10.1007/978-3-319-02895-8_41
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02894-1
Online ISBN: 978-3-319-02895-8
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