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This paper proposes a PolSAR imagery unsupervised classification framework based on consensus similarity network fusion (CSNF), which is generally utilized for biomedical Sciences and for the first time used for PolSAR imagery classification in our work. First, the PolSAR image is divided into superpixels by a fast superpixel segmentation method and five groups of feature vectors are extracted based...
The simple linear iterative clustering (SLIC) method is a popular recently proposed superpixel algorithm. However, it may provide bad superpixels for the synthetic aperture radar (SAR) images due to the influence of speckle and large dynamic range of pixel intensity. In this paper, an improved SLIC algorithm for SAR images is proposed by employing the probability density function (PDF) information...
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