A novel endmember extraction method using modified maximum spectral screening

Endmember extraction is an important task for hyperspectral analysis; the accurate identification of endmembers enables efficient spectral unmixing and classification. In the paper, a new endmember extraction algorithm based on a modified MSS approach with LP error as initial spectrum selection algorithm, and OPD measure as similarity is proposed. The endmembers extracted by modified MSS are more similar than that of MSS algorithm; from the experiments results, it has proved that our proposed method outperforms the existed MSS and N-FINDR algorithms.