Field programmable gate array design of implementing simplex growing algorithm for hyperspectral endmember extraction

Abstract

N-FINDR has been widely used for endmember extraction in hyperspectral imagery. Due to its high computational complexity developing fast computing N-FINDR has become interest. One approach is to design field programmable gate array (FPGA) architecture for N-FINDR to reduce computing time. However, two major issues still need to be addressed. One is that the number of endmembers must be fixed regardless of applications. The other is computation of simplex volumes. This paper investigates a progressive version of N-FINDR, previously known as simplex growing algorithm (SGA) for its FPGA implementation which basically resolves these two issues.