8.2 Successive N-FINDR (SC N-FINDR)

As noted in the s-SC IN-FINDR in Chapter 7, a major issue in its implementation is computational cost that is expected to be very high. In order to mitigate this problem, a sequential version of s-SC IN-FINDR developed in Section 7.2.3.3 can be derived by replacing simultaneous s endmembers carried out in step 5 of the s-SC IN-FINDR with successive p endmember replacements to achieve more computational efficiency at the expense of optimality. The resulting sequential version of p-SC IN-FINDR is referred to as SuCcessive N-FINDR (SC N-FINDR).

Successive N-FINDR (SC N-FINDR)

1. Preprocessing:
a. Let p be the number of endmembers required to generate.
b. Apply a DR transform such as MNF to reduce the data dimensionality from L to p–1, where L is the total number of spectral bands.
2. Initialization:
Let img be a set of initial vectors randomly generated from the data.
3. For img, find img which yields the maximum volume of img defined by (7.3) over all sample vectors r, while fixing other endmembers with and with . That is,

(8.1)

The major difference between ...

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