Title :
Field-Programmable Gate Array Design of Implementing Simplex Growing Algorithm for Hyperspectral Endmember Extraction
Author :
Chein-I Chang ; Wei Xiong ; Chao-Cheng Wu
Author_Institution :
Dept. of Comput. Sci. & Electr. Eng., Univ. of Maryland, Baltimore, MD, USA
Abstract :
N-finder algorithm (N-FINDR) has been widely used for endmember extraction in hyperspectral imagery. Due to its high computational complexity, developing fast computing N-FINDR has received considerable interest, specifically to take advantage of field-programmable gate array (FPGA) architecture in hardware implementation to realize N-FINDR. However, there are two severe drawbacks arising in the nature of N-FINDR design, the number of endmembers, p, which must be fixed once its value is determined in FPGA design and inconsistency in final extracted endmembers caused by different selections of initial endmembers. This paper investigates a progressive version of N-FINDR, previously known as simplex growing algorithm for its FPGA implementation which can resolve these two issues.
Keywords :
computational complexity; feature extraction; field programmable gate arrays; hyperspectral imaging; image processing; N-FINDR; N-finder algorithm; computational complexity; field-programmable gate array design; hyperspectral endmember extraction; hyperspectral imagery; Algorithm design and analysis; Field programmable gate arrays; Hardware; Hyperspectral imaging; Random access memory; Vectors; Endmember extraction algorithm (EEA); N-finder algorithm (N-FINDR); SGA; fast matrix determinant computation; field-programmable gate array (FPGA); real-time fast simplex growing algorithm (SGA) (FSGA) (RT-FSGA); virtual dimensionality (VD);
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2012.2207389