Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1766925 | Advances in Space Research | 2009 | 7 Pages |
Abstract
An unmixing method for hyperspectral Earth observation satellite imagery data is proposed. It is based on a sub-space method with learning process. The proposed method utilizes a sub-space for feature space during unmixing. It is used to be done in a feature space which consists of spectral bands of observation vectors. As the results from the experiments with airborne based hyperspectral imagery data, AVIRIS, it is found that the proposed unmixing is superior to the other existing method in terms of decomposition accuracy and the process time required for the decompositions.
Related Topics
Physical Sciences and Engineering
Earth and Planetary Sciences
Space and Planetary Science
Authors
Kohei Arai, Huahui Chen,