ICE: A new method for the multivariate curve resolution of hyperspectral images
Abstract
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 © 2008 John Wiley & Sons, Ltd.
Citation
Source Title
DOI
ISSN
School
Collection
Related items
Showing items related by title, author, creator and subject.
-
Santich, Norman Ty (2007)As well as the many benefits associated with the evolution of multispectral sensors into hyperspectral sensors there is also a considerable increase in storage space and the computational load to process the data. ...
-
Robinson, Todd Peter (2008)Invasive plants pose serious threats to economic, social and environmental interests throughout the world. Developing strategies for their management requires a range of information that is often impractical to collect ...
-
Dekker, A.; Phinn, S.; Anstee, J.; Bissett, P.; Brando, V.; Casey, B.; Fearns, Peter; Hedley, J.; Klonowski, Wojciech; Lee, Z.; Lynch, Mervyn; Lyons, M.; Mobley, C.; Roelfsema, C. (2011)Science, resource management, and defense need algorithms capable of using airborne or satellite imagery to accurately map bathymetry, water quality, and substrate composition in optically shallow waters. Although a variety ...