Yani Hou, Wenzhong Zhu, Erli Wang
Intelligent Automation & Soft Computing, Vol.25, No.4, pp. 805-814, 2019, DOI:10.31209/2019.100000084
Abstract Hyperspectral remote sensing, with its narrow band imaging, provides the
potential for fine identification of ground objects, and has unique advantages in
mineral detection. However, the image is nonlinear and the pure pixel is scarce,
so using standard spectrum detection will lead to an increase of the number of
false alarm and missed detection. The density peak algorithm performs well in
high-dimensional space and data clustering with irregular category shape. This
paper used the density peak clustering to determine the cluster centers of
various categories of images, and took it as the target spectrum, and More >
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