Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8131928 | Advances in Space Research | 2018 | 11 Pages |
Abstract
A nonparametric method termed as manifold structure preservative (MSP) is proposed in this paper for hyperspectral target detection. MSP transforms the feature space of data to maximize the separation between target and background signals. Moreover, it minimizes the reconstruction error of targets and preserves the topological structure of data in the projected feature space. MSP does not need to consider any distribution for target and background data. So, it can achieve accurate results in real scenarios due to avoiding unreliable assumptions. The proposed MSP detector is compared to several popular detectors and the experiments on a synthetic data and two real hyperspectral images indicate the superior ability of it in target detection.
Related Topics
Physical Sciences and Engineering
Earth and Planetary Sciences
Space and Planetary Science
Authors
Maryam Imani,