A multifeature tensor for remote-sensing target recognition

Publication Type:
Journal Article
IEEE Geoscience and Remote Sensing Letters, 2011, 8 (2), pp. 374 - 378
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In remote-sensing image target recognition, the target or background object is usually transformed to a feature vector, such as a spectral feature vector. However, this kind of vector represents only one pixel of a remote-sensing image that considers the spectral information but ignores the spatial relationship of neighboring pixels (i.e., the local texture and structure). In this letter, we propose a new way to represent an image object as a multifeature tensor that encodes both the spectral and textural information (Gabor function) and then apply the support tensor machine for target recognition. A range of experiments demonstrates that the effectiveness of the proposed method can deliver a high and correct recognition rate with a small number of training samples. © 2006 IEEE.
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