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Journal of Sensors - Volume20162016, Article ID1538973, 12 pages -

Research ArticleDepartment of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong

Received 29 October 2014; Revised 27 January 2015; Accepted 6 February 2015

Academic Editor: Chao-ChengWu

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.

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.





Autor: Zelang Miaoand Wenzhong Shi

Fuente: https://www.hindawi.com/



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