Journal
JOURNAL OF CHEMOMETRICS
Volume 23, Issue 1-2, Pages 101-116Publisher
WILEY
DOI: 10.1002/cem.1198
Keywords
multivariate curve resolution; MNF transform; unmixing; hyperspectral; simplex; convex geometry
Categories
Funding
- National Health and Medical Research Council of Australia
- Australian Synchrotron Research Program Fellowship
- Monash Synchrotron Research Fellowship
Ask authors/readers for more resources
The iterated constrained endmembers (ICE) algorithm is a new method of unmixing hyperspectral images that combines aspects of multivariate curve resolution (MCR) methods in chemometrics and unmixing algorithms in remote sensing. Like many MCR methods, ICE also estimates pure components, or endmembers, via alternating least squares; however, it is explicitly based on a convex geometry model and estimation is carried out in a subspace of reduced dimensionality defined by the minimum noise fraction (MNF) transform. In this paper, we describe the ICE algorithm and its properties. We also illustrate its use on a hyperspectral image of cervical tissue. The unmixing of hyperspectral images presents some unique challenges, and we also outline where further development is required. Copyright (C) 2008 John Wiley & Sons, Ltd.
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