10.5 Random SGA (RSGA)
What VCA is viewed as a sequential version of PPI is exactly what SGA is considered as a sequential version of N-FINDR in the sense that SGA finds one endmember at a time when it grows a series of simplexes with maximal volumes. Similarly, SGA can also be extended to its random version, called RSGA, in the same way as both RSQ N-FINDR and RSC N-FINDR are extended with SGA used in each run.
Random SGA (RSGA)
1. Initialization
a. Assume that the number of endmembers required to be generated is p.
b. Let ε be the given tolerance value of spectral similarity.
c. Set E(1) = 0 and 
.
.
2. Randomly generate two data sample vectors as two initial endmembers, 
.
.
3. Apply SGA to generate p endmembers, denoted by 
.
.
4. If 
, let 
and go to step 2. Otherwise, continue.
, let and go to step 2. Otherwise, continue.
5. Find the intersection of 
. In this case, a spectral measure such as SAM is used to measure spectral similarity. ...
. In this case, a spectral measure such as SAM is used to measure spectral similarity. ...Get Hyperspectral Data Processing: Algorithm Design and Analysis now with the O’Reilly learning platform.
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