a new methodology for spectral-spatial classification of hyperspectral images

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ID: 228706
2016
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Ranked #184 of 205 articles by views in BMC infectious diseases

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Abstract
Recent developments in hyperspectral images have heightened the need for advanced classification methods. To reach this goal, this paper proposed an improved spectral-spatial method for hyperspectral image classification. The proposed method mainly consists of three steps. First, four band selection strategies are proposed to utilize the statistical region merging (SRM) method to segment the hyperspectral image. The segmentation map is subsequently integrated with the pixel-wise classification method to classify the hyperspectral image. Finally, the final classification result is obtained using the decision fusion rule. Validation tests are performed to evaluate the performance of the proposed approach, and the results indicate that the new proposed approach outperforms the state-of-the-art methods.
Reference Key
miao2016journala Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Zelang Miao;Wenzhong Shi
Journal BMC infectious diseases
Year 2016
DOI
10.1155/2016/1538973
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