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基于压缩感知理论的PIE显微成像研究

Microscopic PIE Imaging With Theory of Compressive Sensing

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摘要

为了克服PIE成像中所面临的数据量过大的问题,将压缩感知理论用于PIE成像。将采样到的衍射斑稀疏变换并压缩后,可以显著减少需要存贮的数据量。再现过程中选用子空间匹配追踪算法(SP)或者正交匹配追踪算法(OMP)重构出散射斑的原始分布,用常规的PIE算法进行图像重建。模拟和实验结果均表明,当压缩采样率在30%的时候就能重构出很好的图像。和OMP重构算法相比,SP算法更适合在PIE成像中应用。

Abstract

In order to overcome the problem of large amounts of data in PIE imaging, the theory of compressive sensing is adopted for PIE imaging. Diffraction patterns are sparsified and compressed, which can reduce the amount of data requiring save. The original distribution of scattering spot can be reconstructed with subspace persuit (SP) or orthogonal matching pursuit (OMP) tuning algorithm in the retrieval process, then image reconstruction is realized using regular PIE algorithm. Simulation and experimental results show that the images can be reconstructed perfectly when the compression ratio is 30%. SP algorithm is more appropriate than OMP algorithm for PIE imaging.

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中图分类号:TP751

DOI:10.3788/aos201434.0511008

所属栏目:成像系统

基金项目:江苏省自然科学基金(BK2012548)、江南大学自主科研基金(JUSRP211A20)

收稿日期:2013-12-17

修改稿日期:2014-01-10

网络出版日期:--

作者单位    点击查看

何靖:江南大学理学院光信息科学与技术系, 江苏 无锡 214122
刘诚:江南大学理学院光信息科学与技术系, 江苏 无锡 214122
高淑梅:江南大学理学院光信息科学与技术系, 江苏 无锡 214122
王继成:江南大学理学院光信息科学与技术系, 江苏 无锡 214122
王跃科:江南大学理学院光信息科学与技术系, 江苏 无锡 214122
朱健强:中国科院上海光学精密机械研究所, 上海 201800

联系人作者:何靖(hejingwujia0@163.com)

备注:何靖(1991—),男,硕士研究生,主要从事光学测量方面的研究。

【1】R Gerchberg. Super-resolution through error energy reduction [J]. Journal of Modern Optics, 1974, 21(9): 709-720.

【2】J R Fienup. Phase retrieval algorithms: a comparison [J]. Appl Opt, 1982, 21(15): 2758-2769.

【3】G J Williams, H M Quiney, B B Dhal, et al.. Fresnel coherent diffractive imaging [J]. Phys Rev Lett, 2006, 97(2): 025506.

【4】J C H Spence, U Weierstall, M Howells. Coherence and sampling requirements for diffractive iamging [J]. Ultramicroscopy, 2004, 101(2-4): 149-152.

【5】J M Rodenburg, H M L Faulkner. A phase retrieval algorithm for shifting illumination [J]. Appl Phys Lett, 2004, 85(20): 4795-4797 .

【6】H M L Faulkner, J M Rodenburg. Movable aperture lensless transmission microscopy: a novel phase retrieval algorithm [J]. Phys Rev Lett, 2004, 93(2): 023903.

【7】J M Rodenburg. Ptychography and related diffractive imaging methods [J]. Advances in Imaging and Electron Physics, 2008, 150: 87-184.

【8】A M Maiden, J M Rodenburg, M J Humphry. Optical ptychography: a practical implementation with useful resolution [J]. Opt Lett, 2010, 35(15): 2585-2587.

【9】A M Maiden, M J Humphry, F Zhang, et al.. Superresolution imaging via ptychography [J]. Opt Soc Am A, 2011, 28(4): 604-612.

【10】Wang Baosheng, Gao Shumei, Liu Cheng, et al.. Influence of charge coupled device saturation on PIE imaging [J]. Acta Optica Sinica, 2013, 33(6): 0611001.
王宝升, 高淑梅, 刘诚, 等. 电荷耦合器件饱和效应对PIE成像质量的影响[J]. 光学学报, 2013, 33(6): 0611001.

【11】Pan Xingchen, Lin Qiang, Liu Cheng, et al.. Influence of the partial coherence to the PIE imaging method [J]. Scientia Sinica Phutial, Mechanica & Astronomica, 2012, 42(9): 889-898.
潘兴臣, 林强, 刘诚, 等. 相干性对PIE成像方法的影响[J]. 中国科学: 物理学力学天文学, 2012, 42(9): 889-898.

【12】J N Cederquist, J R Fienup, J C Marron, et al.. Phase retrieval from experimental far-field speckle data [J]. Opt Lett, 1988, 13(8): 619-621.

【13】Huang Linxin, Yao Xin, Cai Dongmei, et al.. A high accuracy and fast iterative algorithm for phase retrieval [J]. Chinese J Lasers, 2010, 37(5): 1218-1221.
黄利新, 姚新, 蔡东梅, 等. 一种快速高精度的相位恢复迭代法[J]. 中国激光, 2010, 37(5): 1218-1221.

【14】E J Candès, J Romberg, T Tao. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information [J]. IEEE Transaction on Information Theory, 2006, 52(2): 489-509.

【15】E J Candès, J Romberg. Quantitative robust uncertainty principles and optimally sparse decompositions [J]. Foundations of Computational Mathematics, 2006, 6(2): 227-254.

【16】D Donoho. Compressed sensing [J]. IEEE Transactions on Information Theory, 2006, 52 (4):1289-1306.

【17】V Goyal, A Fletcher, S Rangan. Compressive sampling and lossy compression [J]. IEEE Signal Processing Magazine, 2008, 25(2): 48-56.

【18】D L Donoho, Y Tsaig. Extensions of compressed sensing [J]. Signal Processing, 2006, 86(3): 549-571.

【19】J A Tropp, A C Gilbert. Signal recovery from random measurements via orthogonal matching pursuit [J]. IEEE Transactions on Information Theory, 2007, 53(12): 4655-4666.

【20】Wei Dai, O Milenkovic. Subspace pursuit for compressive sensing signal reconstruction [J]. IEEE Transactions on Information Theory, 2009, 55(5): 2230-2249.

引用该论文

He Jing,Liu Cheng,Gao Shumei,Wang Jicheng,Wang Yueke,Zhu Jianqiang. Microscopic PIE Imaging With Theory of Compressive Sensing[J]. Acta Optica Sinica, 2014, 34(5): 0511008

何靖,刘诚,高淑梅,王继成,王跃科,朱健强. 基于压缩感知理论的PIE显微成像研究[J]. 光学学报, 2014, 34(5): 0511008

被引情况

【1】杨初平,蔡汶曦,翁嘉文. 加窗截取改善信号非稀疏表达的稀疏性. 激光与光电子学进展, 2015, 52(3): 31002--1

【2】陈文,蒋志龙,刘诚,朱健强. 双光束照明3PIE层析成像. 光学学报, 2016, 36(8): 811002--1

【3】陈文,蒋志龙,刘诚,朱健强. 双光束照明3PIE层析成像. 高功率激光及等离子体物理研究论文集(专题), 2016, 14(1): 811002--1

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