Title :
A new approach to band clustering and selection for hyperspectral imagery
Author :
Haq, Ihsan Ul ; Xu, Xiaojian
Author_Institution :
Sch. of Electron. Inf. Eng., Beihang Univ., Beijing
Abstract :
In this paper a new approach for band selection is introduced based on statistical and geometrical characteristics of band images, where the basic idea is to measure the spread of image data in each band and then clustering the bands in such a way to keep intracluster variance minimum and intercluster variance maximum. For optimal number of bands to be selected, recently developed concept of virtual dimensionality (VD) is used. For endmember extraction, vertex component analysis (VCA) is used. A comparative study is conducted to show the effectiveness of the new approach with other unsupervised band selection methods.
Keywords :
feature extraction; geophysical signal processing; pattern clustering; statistical analysis; band clustering approach; band selection; endmember extraction; geometrical characteristics; hyperspectral imagery; intercluster variance maximum; intracluster variance minimum; statistical characteristic; unsupervised band selection methods; vertex component analysis; virtual dimensionality; Couplings; Data analysis; Data engineering; Data mining; Feature extraction; Hyperspectral imaging; Hyperspectral sensors; Image analysis; Object detection; Remote sensing;
Conference_Titel :
Signal Processing, 2008. ICSP 2008. 9th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2178-7
Electronic_ISBN :
978-1-4244-2179-4
DOI :
10.1109/ICOSP.2008.4697345
