Abstract
Spectral unmixing using hyperspectral data represents a significant step in the evolution of remote decompositional analysis that began with multispectral sensing. It is a consequence of collecting data in greater and greater quantities and the desire to extract more detailed information about the material composition of surfaces. Linear mixing is the key assumption that has permitted well-known algorithms to be adapted to the unmixing problem. In fact, the resemblance of the linear mixing model to system models in other areas has permitted a significant legacy of algorithms from a wide range of applications to be adapted to unmixing. However, it is still unclear whether the assumption of linearity is…
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2Topics & keywords
Topics
Keywords
- Endmember
- Hyperspectral imaging
- Mixing (physics)
- Multispectral image
- Computer science
- Linearity
- Pixel
- Range (aeronautics)
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