Application of spectral features’ ratios for improving classification in partially calibrated hyperspectral imagery: a case study of separating Mediterranean vegetation species | Journal of Real-Time Image Processing
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Application of spectral features’ ratios for improving classification in partially calibrated hyperspectral imagery: a case study of separating Mediterranean vegetation species

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Abstract

Efficient real-time discrimination of image objects is greatly affected by their radiometry, which is only partly accounted for by image scene calibration. Such calibration treats mainly variations in flux density in the generalized imaged scene plane rather than on the objects’ surface. The proposed methodology uses ratios between secondary parameterizations: e.g., absorption features and spectral derivatives. Clustering in the ratios’ parameter space may allow differentiation between image objects despite limitations regarding their relative calibration. The usefulness of this approach was demonstrated in the challenging task of separating Mediterranean vegetation species using imaging spectroscopy.

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Acknowledgment

This research was partly supported by the Israeli Ministry of Science Infrastructure Research Grant scheme (2006–2009).

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Authors and Affiliations

  1. Faculty of Civil & Environmental Engineering, Technion, Israel Institute of Technology, Haifa, 32000, Israel

    Ronit Rud & Maxim Shoshany

  2. Agricultural Research Organization, Institute of Agricultural Engineering, Volcani Center, Bet-Dagan, 50250, Israel

    Ronit Rud, Victor Alchanatis & Yafit Cohen

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  1. Ronit Rud
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  2. Maxim Shoshany
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  3. Victor Alchanatis
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  4. Yafit Cohen
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Correspondence to Ronit Rud.

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Rud, R., Shoshany, M., Alchanatis, V. et al. Application of spectral features’ ratios for improving classification in partially calibrated hyperspectral imagery: a case study of separating Mediterranean vegetation species. J Real-Time Image Proc 1, 143–152 (2006). https://doi.org/10.1007/s11554-006-0015-8

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  • DOI: https://doi.org/10.1007/s11554-006-0015-8

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