Cart (Loading....) | Create Account
Close category search window
 

Enhancing Spectral Unmixing by Local Neighborhood Weights

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
$31 $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

5 Author(s)
Junmin Liu ; Sch. of Math. & Stat., Xi''an Jiaotong Univ., Xi''an, China ; Jiangshe Zhang ; Yuelin Gao ; Chunxia Zhang
more authors

Spectral unmixing is an effective technique to remotely sensed data exploitation. In this paper, appropriate weights in a local neighborhood are designed to enhance spectral unmixing. The weights integrate the spectral and spatial information, and can effectively segment the homogenous and transition areas between different ground cover types. Based on this region-segmentation, pure-pixel-based end-member extraction algorithms are insensitive to the anomalous pixel, and thus perform more robust. In addition, the weights can be used to regularize non-pure-pixel-based unmixing methods, such as nonnegative matrix factorization (NMF). By incorporating the designed local neighborhood weights, a weighted nonnegative matrix factorization (WNMF) algorithm for spectral unmixing is proposed in this paper. Meanwhile, a multiplicative update rule for WNMF is presented, and the monotonic convergence of the rule is proved. Experiments on synthetic and real hyperspectral data validate the effectiveness of the designed weights.

Published in:

Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of  (Volume:5 ,  Issue: 5 )

Date of Publication:

Oct. 2012

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.