电讯技术2018，Vol.58Issue(3)：332-337,6.DOI:10.3969/j.issn.1001-893x.2018.03.016
基于压缩感知的红外遥感图像重构算法分析
Analysis of Infrared Remote Sensing Image Reconstruction Algorithms Based on Compressive Sensing
王蕾强 1周旭1
作者信息
- 1. 中国电子科技集团公司第五十四研究所,石家庄050081
- 折叠
摘要
Abstract
With the rapid development of aerospace remote sensing technology,the performance of sampling and storage devices needs to be improved because of the longer sampling time and larger data of remote sensing image.To resolve the above problem,compressed sensing is introduced into meteorological satellite infrared remote sensing image processing.The performance of Orthogonal Matching Pursuit(OMP) algo-rithm,Gradient Projection for Sparse Reconstruction(GPSR) algorithm,Subspace Pursuit(SP) algorithm and Smoothed l0norm(SL0) algorithm are analyzed by Matlab modeling and simulation.A large number of infrared images are sampled and compressed at different sampling rates,then images are reconstructed with multiple algorithms.Comparative experiments show these algorithms can get the whole infrared image in the lower sampling frequencies,but smoothed l0norm algorithm is better than other algorithms in the accuracy of reconstruction and the runtime.It's proved that compressed sensing has great practical value.关键词
红外遥感图像/压缩感知/平滑l0范数/重构算法Key words
infrared remote sensing image/compressed sensing/smoothed l0norm(SL0)/reconstruction al-gorithm分类
信息技术与安全科学引用本文复制引用
王蕾强,周旭..基于压缩感知的红外遥感图像重构算法分析[J].电讯技术,2018,58(3):332-337,6.
