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《Journal of Anhui Normal University(Natural Science)》 2018-02
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Millimeter Wave Image Sparse Representation and Feature Extraction Based on Global Normed Gradients

ZHANG Ren-ling;HAN Ling-yun;ZHANG Yi-long;CHEN Jian-fei;Department of Mechanical and Electrical Engineering,Anhui Vocational College of Electronic and Information Technology;School of Electronic Engineering and Optoelectronic Technology,Nanjing University of Science and Technology;School of Physics and Electronic Information,Anhui Normal University;School of Optoelectronic Engineering,Nanjing University of Posts and Telecommunications;  
High penetrability,high anti-interference ability,all-time and all-weather advantages make the millimeter wave imaging having wide applications such as in counter-terrorism,environmental monitoring and weather forecast areas,but resolution and target feature extraction technology has been the main bottleneck of the development of millimeter wave imaging. Traditional methods of millimeter wave image denoising and feature extraction tend to cause distortion,which makes it hard to keep the target edge information to extract features. Sparse theory represents structural characteristics of the millimeter wave images using fixed basis function,while effectively remove noise and keep the edge information. Base on global normed gradients,this paper proposed a millimeter wave image sparse representation and feature extraction method,and the simulation imaging results of the experimental data proves the validity and practicability of the proposed methods.
【Fund】: 国家自然科学基金项目(61601237);; 江苏省自然科学基金项目(KB20160901);; 江苏省高校自然科学研究面上项目(16KJB420001)
【CateGory Index】: TP391.41
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