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This randomized trial demonstrates effective dimension reduction in hyperspectral imagery, suggesting improved analysis efficiency.
Presents the formulation of the dimension reduction problem using subset selection as a matrix approximation problem. A heuristic algorithm to solve this problem is presented. Numerical results using LANDSAT and AVIRIS images show that the selected bands are contained in a space that is almost aligned with the first few principal components.
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Vélez-Reyes et al. (1998) studied this question.
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