Based on the geometric properties of a simplex, endmembers can be extracted automatically from a hyperspectral image. To avoid the shortcomings of the N-FINDR algorithm, which requires the dimensions of the data to be one less than the number of endmembers needed, a new volume formula
for the simplex without the requirement of dimension reduction is presented here. We demonstrate that the N-FINDR algorithm is a special case of the new method. Moreover, whether the null vector is included as an endmember has an important effect on the final result of the endmember extraction.
Finally, we compare the new method with previous methods for endmember extraction of hyperspectral data collected by the Advanced Visible and Infrared Imaging Spectrometer (AVIRIS) over Cuprite, Nevada.
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Document Type: Research Article
Key Laboratory of Technology in Geospatial Information Processing and Application Systems, Institute of Electronics, Chinese Academy of Sciences, Beijing, China
School of Electronics and Information Engineering, Beihang University, Beijing, China
Department of Environmental Science, Policy and Management (ESPM), University of California, Berkeley, CA, USA
Publication date: 2010-04-01
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