Improved Real-Time Fast Simplex Growing Algorithm for Finding Endmembers in Hyperspectral Data and its FPGA architecture

This paper proposes a fast-processing algorithm for finding endmembers in hyperspectral image data and it’s FPGA architecture. The proposed algorithm named as Improved Real-Time Fast Simplex Growing Algorithm (IRT-FSGA) removes redundant computation for the pixels which do not qualify as endmember replacements and thereby achieves a significant reduction in computation time over the RT-FSGA algorithm. The improvement obtained is without compromising on the accuracy of the endmembers found. FPGA implementation results of the designed architecture show that the proposed IRT-FSGA achieves 33× improvement in performance at the cost of only a small area overhead. Thus, it is potentially useful in real-time applications which have stringent throughput and power requirements.