Multiscale Superpixel-Based Sparse Representation for Hyperspectral Image Classification
AbstractRecently, superpixel segmentation has been proven to be a powerful tool for hyperspectral image (HSI) classification. Nonetheless, the selection of the optimal superpixel size is a nontrivial task. In addition, compared with single-scale superpixel segmentation, the same image segmented on a different scale can obtain different structure information. To overcome such a drawback also utilizing the structural information, a multiscale superpixel-based sparse representation (MSSR) algorithm for the HSI classification is proposed. Specifically, a modified segmentation strategy of multiscale superpixels is firstly applied on the HSI. Once the superpixels on different scales are obtained, the joint sparse representation classification is used to classify the multiscale superpixels. Furthermore, majority voting is utilized to fuse the labels of different scale superpixels and to obtain the final classification result. Two merits are realized by the MSSR. First, multiscale information fusion can more effectively explore the spatial information of HSI. Second, in the multiscale superpixel segmentation, except for the first scale, the superpixel number on a different scale for different HSI datasets can be adaptively changed based on the spatial complexity of the corresponding HSI. Experiments on four real HSI datasets demonstrate the qualitative and quantitative superiority of the proposed MSSR algorithm over several well-known classifiers. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Zhang, S.; Li, S.; Fu, W.; Fang, L. Multiscale Superpixel-Based Sparse Representation for Hyperspectral Image Classification . Remote Sens. 2017, 9, 139.
Zhang S, Li S, Fu W, Fang L. Multiscale Superpixel-Based Sparse Representation for Hyperspectral Image Classification . Remote Sensing. 2017; 9(2):139.Chicago/Turabian Style
Zhang, Shuzhen; Li, Shutao; Fu, Wei; Fang, Leiyuan. 2017. "Multiscale Superpixel-Based Sparse Representation for Hyperspectral Image Classification ." Remote Sens. 9, no. 2: 139.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.