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This paper presents a new classification framework for the fusion of hyperspectral and LiDAR data. The proposed approach aims at exploiting the complementarity of the features, i.e., textural features in the hyperspectral data and the height features in the LiDAR data, respectively. In this work, we use a morphological component analysis (MCA) method for textural feature extraction. The classification...
In this letter, we present an efficient parallel implementation of composite kernels in support vector machines (SVMs) for hyperspectral image (HSI) classification. Our implementation makes effective use of commodity graphics processing units (GPUs). Specifically, we port the calculation of composite kernels to GPUs, perform intensive computations based on NVidia's compute unified device architecture,...
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