Rapid matching algorithm for hyperspectral image based on norm sifting

We propose a rapid spectral matching method by lowering number of comparisons, processing time can be saved. Firstly, 1-norm is chosen as length measure of spectrum, and with this criterion, a 1-norm database is built. Secondly, a subspace is constructed from the whole reference library by retaining the references with the most similar 1-norm values. Finally, matching operations are performed in the subspace to obtain the match result. Simulations of geological mapping with ASTER spectral library show that the proposed method can significantly reduce processing time and enhance accuracy compared with traditional and dimension reduction methods.