期刊
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
卷 16, 期 2, 页码 246-250出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2018.2871273
关键词
Classification; guided filter (GF); hyperspectral image (HSI); multiscale; sparse representation; spatial-spectral; superpixel
类别
资金
- Scientific and Technological Research Council of Turkey [215E179]
We propose a spatial-spectral hyperspectral image classification method based on multiscale superpixels and guided filter (MSS-GF). In order to use spatial information effectively, MSSs are used to get local information from different region scales. Sparse representation classifier is used to generate classification maps for each region scale. Then, multiple binary probability maps are obtained for each of the classification maps. Adding GE denoises the classification results and then improves the classification accuracy. Finally, the class label of each pixel is determined by majority voting rule.
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