Manifold structure preservative for hyperspectral target detection |
| |
Authors: | Maryam Imani |
| |
Affiliation: | Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran |
| |
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. |
| |
Keywords: | Local structure Feature transformation Target detection Hyperspectral image |
本文献已被 ScienceDirect 等数据库收录! |