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http://hdl.handle.net/10397/62450
Title: | A new methodology for spectral-spatial classification of hyperspectral images | Authors: | Miao, Z Shi, WZ |
Issue Date: | 2016 | Source: | Journal of sensors, 2016, 1538973 | 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. | Publisher: | Hindawi Publishing Corporation | Journal: | Journal of sensors | ISSN: | 1687-725X | EISSN: | 1687-7268 | DOI: | 10.1155/2016/1538973 | Rights: | Copyright © 2016 Zelang Miao and Wenzhong Shi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The following article: Miao, Z., & Shi, W. (2016). A new methodology for spectral-spatial classification of hyperspectral images. Journal of Sensors, 2016, is available at https//doi.org/10.1155/2016/1538973 |
Appears in Collections: | Journal/Magazine Article |
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