Paper
1 September 2006 Automatic algorithms for endmember extraction
Author Affiliations +
Abstract
Endmenber extraction has received increasing interests in hyperspectral image analysis. Two major issues are of interest. One is determination of endmembers, p, required to be generated and the other is generation of initial endmembers. Since most endmember extraction algorithms (EEAs) use randomly generated vectors as their initial endmembers to initialize their algorithms, their final generated endmembers are generally determined by these random initial endmembers. As a result, a different set of random initial endmembers may well likely produce a different final set of desired endmembers. This paper converts this disadvantage to an advantage and further resolves the above-mentioned two issues. Due to the random nature of initial endmembers, the proposed idea is to implement an EEA as a random algorithm so that a single run using a random set of initial endmembers is considered as a realization of a random algorithm. As a result, if an EEA is implemented several times with different sets of random initial endmembers, the intersection of their final generated endmembers in all runs should contain the desired endmembers. An EEA is then terminated when their produced intersections converge to the same set of desired endmembers. In this case, there is no need to determine the p. An EEA implemented in such a manner is called automatic EEA (AEEA). Two commonly used EEAs, pixel purity index (PPI) and N-finder algorithm (N-FINDR), are extended to AEEAs along with a new automatic ICA-based EEA. Experimental results demonstrate that the AEEA performs at least as well as their counterparts.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chao-Cheng Wu and Chein-I Chang "Automatic algorithms for endmember extraction", Proc. SPIE 6302, Imaging Spectrometry XI, 63020E (1 September 2006); https://doi.org/10.1117/12.681653
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Minerals

Reflectivity

Algorithm development

Hyperspectral imaging

Image analysis

Signal to noise ratio

Error analysis

Back to Top