Journal
NEURAL PROCESSING LETTERS
Volume 43, Issue 3, Pages 805-821Publisher
SPRINGER
DOI: 10.1007/s11063-015-9447-0
Keywords
Remote sensing image; Projection matrix; Support vector machine; Image classification; Kernel method
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Funding
- National Natural Science Foundation of P.R. China [61271386]
- Graduates' Research Innovation Program of Higher Education of Jiangsu Province of P.R. China [CXZZ13-0239]
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A new and efficient classification model is introduced in this paper. The proposed model enjoys the information of null space of within-class and range space of within-class. And the proposed model aims at defining a reliable spatial analysis criterion for the remote sensing image, taking advantage of the differences in different areas. Finally, by incorporating fisher linear discriminant analysis and support vector machine (or K-nearest neighbor) classifier among image pixels, the model obtained more accurate classification results.
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