Classification of hyperspectral image via spatial-spectral manifold reconstruction
- Resource Type
- Conference
- Authors
- Yang, Yaqiong; Huang, Hong; Luo, Fulin
- Source
- 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) Geoscience and Remote Sensing Symposium (IGARSS), 2016 IEEE International. :2442-2445 Jul, 2016
- Subject
- General Topics for Engineers
Signal Processing and Analysis
Image reconstruction
Manifolds
Hyperspectral imaging
Support vector machines
Image classification
Information filtering
hyperspectral image classification
spatial-spectral information
mean filter
manifold reconstruction
- Language
- ISSN
- 2153-7003
To utilize the spatial information and manifold structure in hyperspectral image (HSI), we propose a spatial-spectral manifold reconstruction classifier (SSMRC) for HSI classification in this paper. The SSMRC method firstly uses a mean filter to combine the spatial neighborhood information. Then the manifold reconstruction error utilizes as a measurement of how well a data point resides on a manifold, and the class label can be assigned with the minimum reconstruction error. It makes full use of spatial information and discriminating manifold structure in HSI, and the classification ability is further improved. The effectiveness of the proposed method is verified on real HSI data set with promising results.