By Topic

Unsupervised band selection method based on improved N-FINDR algorithm for spectral unmixing

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Liguo Wang ; Dept. of Inf. Eng., Harbin Inst. of Technol., Heilongjiang, China ; Ye Zhang ; Yanfeng Gu

Hyperspectral imagery (HSI) has high spectral dimensionality which presents a serious challenge to HSI processing, and so reduction of dimensionality is necessary. Band selection (BS) is one of the categories of dimensionality reduction methods. Existing BS methods have expensive cost, need prior information or only cater for classification. In order to get an efficient and unsupervised BS method for spectral unmixing, two aspects work are done. First, original N-FINDR algorithm is greatly improved by substituting volume calculation for distance test. Second, the improved N-FINDR algorithm is used to construct an unsupervised BS method for spectral unmixing. Both theory and experiments prove that the new unsupervised BS method is very effective

Published in:

2006 1st International Symposium on Systems and Control in Aerospace and Astronautics

Date of Conference:

19-21 Jan. 2006