A Spectral-Texture Kernel-Based Classification Method for Hyperspectral Images
نویسندگان
چکیده
منابع مشابه
A Spectral-Texture Kernel-Based Classification Method for Hyperspectral Images
Classification of hyperspectral images always suffers from high dimensionality and very limited labeled samples. Recently, the spectral-spatial classification has attracted considerable attention and can achieve higher classification accuracy and smoother classification maps. In this paper, a novel spectral-spatial classification method for hyperspectral images by using kernel methods is invest...
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Many researches have demonstrated that the spatial information can play an important role in the classification of hyperspectral imagery. This study proposes a modified spectral–spatial classification approach for improving the spectral–spatial classification of hyperspectral images. In the proposed method ten spatial/texture features, using mean, standard deviation, contrast, homogeneity, corr...
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Hyperspectral sensors are important tools in monitoring the phenomena of the Earth due to the acquisition of a large number of spectral bands. Hyperspectral image classification is one of the most important fields of hyperspectral data processing, and so far there have been many attempts to increase its accuracy. Spatial features are important due to their ability to increase classification acc...
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2016
ISSN: 2072-4292
DOI: 10.3390/rs8110919