Abstract
This paper compares several nonlinear models recently introduced for hyperspectral image unmixing. All these models consist of bilinear models that have shown interesting properties for hyperspectral images subjected to multipath effects. The first part of this paper presents different algorithms allowing the parameters of these models to be estimated. The relevance and flexibility of these models for spectral unmixing are then investigated by comparing the reconstruction errors and spectral angle mappers computed from synthetic and real dataset. This kind of study is important to determine which mixture model should be used in practical applications for hyper-spectral image unmixing.
Original language | English |
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Title of host publication | 2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS) |
Publisher | IEEE |
ISBN (Electronic) | 9781457722011 |
ISBN (Print) | 9781457722028 |
DOIs | |
Publication status | Published - 18 Nov 2011 |
Event | 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing 2011 - Lisbon, Portugal Duration: 6 Jun 2011 → 9 Jun 2011 |
Conference
Conference | 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing 2011 |
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Abbreviated title | WHISPERS 2011 |
Country/Territory | Portugal |
City | Lisbon |
Period | 6/06/11 → 9/06/11 |
Keywords
- Hyperspectral imagery
- linear model
- nonlinear model
- unmixing
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Signal Processing