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Object reconstruction by compressive sensing based normalized ghost imaging
Guo, S.-X.; C. Zhang; J.-S. Cao; F. Zhong and F.-L. Gao
2015
发表期刊Guangxue Jingmi Gongcheng/Optics and Precision Engineering
卷号23期号:1页码:288-294
摘要According to compressive sensing theory, a compressive sensing based normalized ghost imaging method was proposed. Firstly, the measurements of a bucket detector were normalized, and the measurement matrix was constructed with speckle fields. Then, the object image was reconstructed with a low number of measurements by adopting orthogonal matching pursuit method. Several experiments were performed by using gray-scale images and binary images respectively as the imaging targets and the Peak Signal to Noise Ratio(PSNR) as the yardstick. The reconstruction effects were quantized and compared for traditional Ghost Imaging(GI), Normalized Ghost Imaging(NGI) and Compressive Sensing based Normalized Ghost Imaging(CSNGI) respectively. The simulation results indicate that the PSNR of CSNGI is about 6 dB and 2 dB higher than those of GI and NGI on gray-scale images with more details, and 3.4-4.3 dB and 5.2-6.5 dB higher than those of NGI and GI for binary images with less details, respectively. Finally, the actual speckle field measured by Charge Coupled Devices(CCDs) was used to construct the measurement matrix, and the experiment results also further indicate that the CSNGI improves the reconstruction quality greatly. , 2015, Chinese Academy of Sciences. All right reserved.
文章类型期刊论文
收录类别EI
文献类型期刊论文
条目标识符http://ir.ciomp.ac.cn/handle/181722/56037
专题中科院长春光机所知识产出
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Guo, S.-X.,C. Zhang,J.-S. Cao,et al. Object reconstruction by compressive sensing based normalized ghost imaging[J]. Guangxue Jingmi Gongcheng/Optics and Precision Engineering,2015,23(1):288-294.
APA Guo, S.-X.,C. Zhang,J.-S. Cao,&F. Zhong and F.-L. Gao.(2015).Object reconstruction by compressive sensing based normalized ghost imaging.Guangxue Jingmi Gongcheng/Optics and Precision Engineering,23(1),288-294.
MLA Guo, S.-X.,et al."Object reconstruction by compressive sensing based normalized ghost imaging".Guangxue Jingmi Gongcheng/Optics and Precision Engineering 23.1(2015):288-294.
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