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A new endmember extraction algorithm based on orthogonal bases of subspace formed by endmembers

A new algorithm for decomposition of mixed pixels based on orthogonal bases of data space is proposed in this paper. It extracts endmembers sequentially by adding a new vertex of the simplex with the maximum volume every time. It can avoid the dilemma in traditional simplex-based endmember extraction algorithms such as N-FINDR that it generally produces different sets of final endmembers if different initial conditions are used. Meanwhile, at each step of the searching process, the calculation of a simplex volume based on determinant of a matrix is replaced by the one based on the norm products of a set of orthogonal bases, which results in a tremendous reduction of computational complexity. Moreover, with this set of orthogonal bases, the proposed algorithm can also determine the proper number of endmembers and finish the unmixing of the original images which cannot be done by the traditional endmember extraction algorithms. Experimental results of practical remote sensing images demonstrate that the algorithm proposed in this paper is a fast and accurate algorithm for the decomposition of mixed pixels.