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Wavelet domain statistical hyperspectral soil texture classification

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3 Author(s)
Xudong Zhang ; Dept. of Electr. & Comput. Eng., Mississippi State Univ., MS, USA ; Younan, N.H. ; O'Hara, C.G.

This communication presents an automatic soil texture classification system using hyperspectral soil signatures and wavelet-based statistical models. Previous soil texture classification systems are closely related to texture classification methods, where images are used for training and testing. In this study, we develop a novel system using hyperspectral soil textures, which provide rich information and intrinsic properties about soil textures, where two wavelet-domain statistical models, namely, the maximum-likelihood and hidden Markov models, are incorporated for the classification task. Experimental results show that these methods are both reliable and robust.

Published in:

Geoscience and Remote Sensing, IEEE Transactions on  (Volume:43 ,  Issue: 3 )

Date of Publication:

March 2005

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