A new approach based on orthogonal bases of data space to decomposition of mixed pixels for hyperspectral imagery |
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Authors: | XueTao Tao Bin Wang LiMing Zhang |
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Affiliation: | (1) Department of Electronics Engineering, Fudan University, Shanghai, 200433, China;(2) Key Laboratory of Wave Scattering and Remote Sensing Information (Ministry of Education), Fudan University, Shanghai, 200433, China |
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Abstract: | A new algorithm for decomposition of mixed pixels based on orthogonal bases of data space is proposed in this paper. It is
a simplex-based method which extracts endmembers sequentially using computations of largest simplex volumes. At each searching
step of this extraction algorithm, searching for the simplex with the largest volume is equivalent to searching for a new
orthogonal basis which has the largest norm. The new endmember corresponds to the new basis with the largest norm. This algorithm
runs very fast and can also 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. 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 the traditional simplex-based algorithms cannot do by themselves. Experimental results of both
artificial simulated images and practical remote sensing images demonstrate the algorithm proposed in this paper is a fast
and accurate algorithm for the decomposition of mixed pixels. |
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Keywords: | decomposition of mixed pixels simplex-based method endmember extraction N-FINDR SGA orthogonal bases hyperspectral data |
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