Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Real-Time Target Detection Architecture Based on Reduced Complexity Hyperspe | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 438051 14 pages doi 2008 438051 Research Article Real-Time Target Detection Architecture Based on Reduced Complexity Hyperspectral Processing Kyoung-Su Park 1 Shung Han Cho 1 Sangjin Hong 1 and We-Duke Cho2 1 Mobile Systems Design Laboratory Department of Electrical and Computer Engineering College of Engineering and Apllied Sciences Stony Brook University-SUNY Stony Brook NY 11794-2350 USA 2 Division of Electrical Computer Engineering College of Information Technology Ajou University Suwon 443-749 South Korea Correspondence should be addressed to Sangjin Hong snjhong@ Received 30 May 2007 Revised 10 October 2007 Accepted 28 March 2008 Recommended by Mark Kahrs 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 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. Copyright 2008 Kyoung-Su Park et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. INTRODUCTION Hyperspectral processing technology is a powerful tool for detecting
