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Wavelet packets for time-frequency analysis of multispectral imagery

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Abstract

Multispectral geospatial image sets retain the scene’s spatial and spectral information. To jointly use both of them for analysis purposes, we propose to extend the concept of wavelet packets, by introducing a new integrated multispectral entropy function. Each spectral band is individually decomposed by the wavelet packets transform, and then the entropy term is jointly guided by information from all bands, simultaneously. Finally, the wavelet packets coefficients undergo a dimension reduction process. We present examples of this theory applied to hyperspectral satellite imagery.

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Acknowledgments

This work presented in this paper was supported in part by NSF (CBET 0854233), by NGA (HM 15820810009), by NIH/DFG (EH 405/1-1/575910), by WWTF (VRG 12-009), and by MURI-ARO (W911NF-09-0383).

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Authors and Affiliations

  1. Department of Mathematics, Norbert Wiener Center, University of Maryland, College Park, MD, 20742, USA

    John J. Benedetto & Wojciech Czaja

  2. Faculty of Mathematics, University of Vienna, Oskar-Morgenstern-Platz 1, 1090 , Vienna, Austria

    Martin Ehler

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  1. John J. Benedetto
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  2. Wojciech Czaja
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  3. Martin Ehler
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Correspondence to John J. Benedetto.

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Benedetto, J.J., Czaja, W. & Ehler, M. Wavelet packets for time-frequency analysis of multispectral imagery. Int J Geomath 4, 137–154 (2013). https://doi.org/10.1007/s13137-013-0052-y

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