Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 399-403, 2016
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B7/399/2016/
doi:10.5194/isprs-archives-XLI-B7-399-2016
 
21 Jun 2016
A KERNEL METHOD BASED ON TOPIC MODEL FOR VERY HIGH SPATIAL RESOLUTION (VHSR) REMOTE SENSING IMAGE CLASSIFICATION
Linmei Wu1, Li Shen1,2, and Zhipeng Li1 1Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 610031, China
2State-province Joint Engineering Laboratory of Spatial Information Technology for High-Speed Railway Safety, Southwest Jiaotong University, Chengdu 610031, China
Keywords: VHSR remote sensing image, Classification, Support vector machine (SVM), Composite kernel, Latent Dirichlet allocation (LDA), Structure, Spatial, Spectral Abstract. A kernel-based method for very high spatial resolution remote sensing image classification is proposed in this article. The new kernel method is based on spectral-spatial information and structure information as well, which is acquired from topic model, Latent Dirichlet Allocation model. The final kernel function is defined as K = u1Kspec + u2Kspat + u3Kstru, in which Kspec, Kspat, Kstru are radial basis function (RBF) and u1 + u2 + u3 = 1. In the experiment, comparison with three other kernel methods, including the spectral-based, the spectral- and spatial-based and the spectral- and structure-based method, is provided for a panchromatic QuickBird image of a suburban area with a size of 900 × 900 pixels and spatial resolution of 0.6 m. The result shows that the overall accuracy of the spectral- and structure-based kernel method is 80 %, which is higher than the spectral-based kernel method, as well as the spectral- and spatial-based which accuracy respectively is 67 % and 74 %. What's more, the accuracy of the proposed composite kernel method that jointly uses the spectral, spatial, and structure information is highest among the four methods which is increased to 83 %. On the other hand, the result of the experiment also verifies the validity of the expression of structure information about the remote sensing image.
Conference paper (PDF, 1437 KB)


Citation: Wu, L., Shen, L., and Li, Z.: A KERNEL METHOD BASED ON TOPIC MODEL FOR VERY HIGH SPATIAL RESOLUTION (VHSR) REMOTE SENSING IMAGE CLASSIFICATION, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 399-403, doi:10.5194/isprs-archives-XLI-B7-399-2016, 2016.

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