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Endmember finding has become increasingly important in hyperspectral data exploitation because endmembers can be used to specify unknown particular spectral classes. Pixel purity index (PPI) and N-finder algorithm (N-FINDR) are probably the two most widely used techniques for this purpose where many currently available endmember finding algorithms are indeed derived from these two algorithms and can...
Fully constrained least squares (FCLS) method has been widely used in linear spectral mixture analysis (LSMA). This paper presents a progressive endmember growing method by FCLS, to be called Endmember Growing FCLS (EG-FCLS). Its idea is derived from a commonly used endmember finding algorithm, Simplex Growing Algorithm (SGA) where the criterion of finding maximal simplex volume is replaced by least...
Fully constrained least squares (FCLS) method has been widely used in linear spectral mixture analysis (LSMA). This paper presents two versions of FCLS, to be called SeQuential FCLS (SQ-FCLS) and SuCcessive FCLS (SC-FCLS) to find endmembers. In order to address random issues in initial conditions, two versions of FCLS, Iterative FCLS (I-FLCS) and Random FCLS (RFCLS) are also developed.
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