Generalized Aggregation of Sparse Coded Multi-Spectra for Satellite Scene Classification
AbstractSatellite scene classification is challenging because of the high variability inherent in satellite data. Although rapid progress in remote sensing techniques has been witnessed in recent years, the resolution of the available satellite images remains limited compared with the general images acquired using a common camera. On the other hand, a satellite image usually has a greater number of spectral bands than a general image, thereby permitting the multi-spectral analysis of different land materials and promoting low-resolution satellite scene recognition. This study advocates multi-spectral analysis and explores the middle-level statistics of spectral information for satellite scene representation instead of using spatial analysis. This approach is widely utilized in general image and natural scene classification and achieved promising recognition performance for different applications. The proposed multi-spectral analysis firstly learns the multi-spectral prototypes (codebook) for representing any pixel-wise spectral data, and then, based on the learned codebook, a sparse coded spectral vector can be obtained with machine learning techniques. Furthermore, in order to combine the set of coded spectral vectors in a satellite scene image, we propose a hybrid aggregation (pooling) approach, instead of conventional averaging and max pooling, which includes the benefits of the two existing methods, but avoids extremely noisy coded values. Experiments on three satellite datasets validated that the performance of our proposed approach is very impressive compared with the state-of-the-art methods for satellite scene classification. 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
Han, X.-H.; Chen, Y.-W. Generalized Aggregation of Sparse Coded Multi-Spectra for Satellite Scene Classification. ISPRS Int. J. Geo-Inf. 2017, 6, 175.
Han X-H, Chen Y-W. Generalized Aggregation of Sparse Coded Multi-Spectra for Satellite Scene Classification. ISPRS International Journal of Geo-Information. 2017; 6(6):175.Chicago/Turabian Style
Han, Xian-Hua; Chen, Yen-wei. 2017. "Generalized Aggregation of Sparse Coded Multi-Spectra for Satellite Scene Classification." ISPRS Int. J. Geo-Inf. 6, no. 6: 175.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.