Abstract
Automatic target generation process (ATGP) has been used in a wide range of applications in hyperspectral image analysis. It performs a sequence of orthogonal subspace projections to extract potential targets of interest. This letter presents a recursive version of the ATGP, which is referred to as the recursive ATGP (RATGP) and has three advantages over the ATGP as follows: 1) there is no need of inverting a matrix as the ATGP does for finding each new target; 2) there is a significant reduction in the computational complexity in the hardware design due to its recursive structure; and 3) there is an automatic stopping rule that can be derived by the Neyman–Pearson detection theory to terminate the algorithm.
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