Real-Time Target Detection Architecture Based on Reduced Complexity Hyperspectral Processing. (8th April 2008)

• Record Type: Journal Article
• Authors: Park Park, Kyoung-Su Kyoung-Su; Cho Cho, Shung Han Shung Han; Hong Hong, Sangjin Sangjin; Cho Cho, We-Duke We-Duke
• Other Names: Kahrs Kahrs Mark Mark Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2008(2008)
• Publication Date: 2008-04-08
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2008/438051
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : This paper presents a real-time target detection architecture for hyperspectral image processing. The architecture is based on a reduced complexity algorithm for high-throughput applications.We propose an efficient pipelined processing element architecture and a scalable multiple-processing element architecture by exploiting data partitioning. We present a processing unit modeling based on the data reduction algorithm in hyperspectral image processing and propose computing structure, that is, to optimize memory usage and eliminates memory bottleneck. We investigate the interconnection topology for the multipleprocessing element architecture to improve the speed. The proposed architecture is designed and implemented in FPGA to illustrate the relationship between hardware complexity and execution throughput of hyperspectral image processing for target detection.