A New Methodology for Spectral-Spatial Classification of Hyperspectral Images. (11th November 2015)

• Record Type: Journal Article
• Authors: Miao, Zelang; Shi, Wenzhong
• Other Names: Wu Chao-Cheng Academic Editor.
• Is Part Of: Journal of sensors. Volume 2016(2016)
• Publication Date: 2015-11-11
• Subjects: Detectors -- Periodicals; 681.205
• DOI: 10.1155/2016/1538973
• Languages: English
• ISSNs: 1687-725X

Abstract

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.