Journal
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
Volume 10, Issue 5, Pages 1229-1233Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2012.2236819
Keywords
Band selection; complex networks; hyperspectral imagery; topology feature measurement
Categories
Funding
- National Natural Science Foundation of China [61071134]
- Innovation Program of Shanghai Municipal Education Commission [13ZZ005]
- Research Fund for Doctoral Program of Higher Education of China [20110071110018]
Ask authors/readers for more resources
In recent years, band selection is becoming a popular approach to reduce the dimensionality of hyperspectral data while preserving the desired information for target detection and classification analysis. This letter presents a new method for unsupervised band selection by transforming the hyperspectral data into complex networks. By analyzing the networks' topological feature corresponding to each band, one can easily evaluate the statistical characteristics and intrinsic properties of the signals. The proposed method searches for the network set which is most qualified for demarcating and identifying different substance signatures, and then, the network set's corresponding bands are regarded as the descried output results. This network measure is a new criterion for band selection. Experimental results demonstrate that the proposed method can acquire satisfactory results when compared with traditional methods.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available