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    A Noise-Resistant Superpixel Segmentation Algorithm for Hyperspectral Images

    Peng Fu1,2, Qianqian Xu1, Jieyu Zhang3, Leilei Geng4,*

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 509-515, 2019, DOI:10.32604/cmc.2019.05250

    Abstract The superpixel segmentation has been widely applied in many computer vision and image process applications. In recent years, amount of superpixel segmentation algorithms have been proposed. However, most of the current algorithms are designed for natural images with little noise corrupted. In order to apply the superpixel algorithms to hyperspectral images which are always seriously polluted by noise, we propose a noise-resistant superpixel segmentation (NRSS) algorithm in this paper. In the proposed NRSS, the spectral signatures are first transformed into frequency domain to enhance the noise robustness; then the two widely spectral similarity measures-spectral angle mapper (SAM) and spectral information… More >

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