传感技术学报2017，Vol.30Issue(1)：94-100,7.DOI:10.3969/j.issn.1004-1699.2017.01.018
基于DFT基的矿井视频监控图像分块压缩感知方法∗
The Block Compressed Sensing of Mine Monitoring Images Based on DFT Basis
摘要
Abstract
To address the problem that the captured videos exist low resolution with noise and long transmission time by using conventional methods of images sampling for mine videos,based on compressed sensing,the algorithm of block compressed sensing for mine videos is proposed. By establishing model of block compressed sensing in mine monitoring videos,the proposed method uses sparse random matrix to sample mine images on sensing nodes. Then,it employs orthogonal matching pursuit ( OMP ) algorithm to reconstruct image on monitoring center. The results indicate that the proposed method compares favorably with existing schemes at lower reconstruction error, shorter reconstruction time and less sampled data.The Peak Signal￣to￣Noise Ratio(PSNR)of the algorithm is 8 dB~10 dB higher than that of the method using Scrambled Hadamard matrix,and simultaneously is improved by 1 dB~4 dB in comparison with that of the algorithm which base on wavelet basis,but the time is shortened at least 80%.关键词
矿井视频监控图像/分块压缩感知/离散傅里叶变换矩阵/正交匹配追踪算法/峰值信噪比Key words
mine monitoring images/block compressed sensing/DFT basis/OMP algorithm/PSNR分类
信息技术与安全科学引用本文复制引用
张帆,闫秀秀..基于DFT基的矿井视频监控图像分块压缩感知方法∗[J].传感技术学报,2017,30(1):94-100,7.基金项目
国家自然科学基金重点项目(51134024)；国家863计划项目(2012AA062203)；中央高校基本科研业务基金项目(2014YJ01) （51134024）
