Hyperspectral image classification based on Monte Carlo feature reduction method
نویسندگان
چکیده
منابع مشابه
Hyperspectral image classification based on volumetric texture and dimensionality reduction
A novel approach using volumetric texture and reduced-spectral features is presented for hyperspectral image classification. Using this approach, the volumetric textural features were extracted by volumetric gray-level co-occurrence matrices (VGLCM). The spectral features were extracted by minimum estimated abundance covariance (MEAC) and linear prediction (LP)-based band selection, and a semi-...
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Dimensionality reduction (DR) of image features plays an important role in image retrieval and classification tasks. Recently, two types of methods have been proposed to improve the both the accuracy and efficiency for the dimensionality reduction problem. One uses Non-negative matrix factorization (NMF) to describe the image distribution on the space of base matrix. Another one for dimension r...
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ژورنال
عنوان ژورنال: Journal of Infrared and Millimeter Waves
سال: 2013
ISSN: 1001-9014
DOI: 10.3724/sp.j.1010.2013.00062