A Research on the Combination Strategies of Multiple Features for Hyperspectral Remote Sensing Image Classification
Joint Authors
Ma, Yuntao
Li, Ruren
Yang, Guang
Sun, Lishuang
Wang, Jingli
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-05-13
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
It has been common to employ multiple features in the identification of the images acquired by hyperspectral remote sensing sensors, since more features give more information and have complementary properties.
Few studies have discussed the combination strategies of multiple feature groups.
This study made a systematic research on this problem.
We extracted different groups of features from the initial hyperspectral images and tried different combination scenarios.
We integrated spectral features with different textural features and employed different dimensionality reduction algorithms.
Experimental results on three widely used hyperspectral remote sensing images suggested that “dimensionality reduction before combination” performed better especially when textural features performed well.
The study further compared different combination frameworks of multiple feature groups, including direct combination, manifold learning, and multiple kernel method.
The experimental results demonstrated the effectiveness of direct combination with an autoweight calculation.
American Psychological Association (APA)
Ma, Yuntao& Li, Ruren& Yang, Guang& Sun, Lishuang& Wang, Jingli. 2018. A Research on the Combination Strategies of Multiple Features for Hyperspectral Remote Sensing Image Classification. Journal of Sensors،Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1201990
Modern Language Association (MLA)
Ma, Yuntao…[et al.]. A Research on the Combination Strategies of Multiple Features for Hyperspectral Remote Sensing Image Classification. Journal of Sensors No. 2018 (2018), pp.1-14.
https://search.emarefa.net/detail/BIM-1201990
American Medical Association (AMA)
Ma, Yuntao& Li, Ruren& Yang, Guang& Sun, Lishuang& Wang, Jingli. A Research on the Combination Strategies of Multiple Features for Hyperspectral Remote Sensing Image Classification. Journal of Sensors. 2018. Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1201990
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1201990