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《Laser & Infrared》 2016-01
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Hyperspectral image target detection algorithm based on constrained maximum correlation coefficient

WANG Cai-ling;HU Bing-liang;WANG Hong-wei;WEN Jia;LI Xiang-juan;Xi'an Shiyou University,School of Computer Science;Xi'an Institute of Optics and Precision Mechanics of CAS;Engineering University of CAPF;Tianjin Polytechnic University,School of Electronics and Information Engineering;  
Hyperspectral remote sensing image has high-resolution spatial information and contains continuous spectrum information,and it has unique advantage in the field of target detection. Target detection techniques based on hyperspectral image are one of the important areas in remote sensing theory and application. Starting from the concept of correlation coefficient in statistics,the target detection algorithm of hyperspectral image based on constrained maximum correlation coefficient is proposed. Different amounts of sub-pixel targets and goals were gotten by adding the target spectrum in the real hyperspectral image,and the real hyperspectral images of large targets were obtained by hyperspectral imager. By comparing constrained energy minimum method and the proposed method,the experiment results show that the proposed algorithm has more robust performance for large target detection.
【Fund】: 国家自然科学基金项目(No.41301382;No.41301480;No.61401439);; 教育部人文社会科学研究青年基金项目(No.14YJCZH172);; 江苏省自然基金项目(No.20142BAB207007);; 西安石油大学创新基金项目(No.YS29031606)资助
【CateGory Index】: TP751
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