同轴压缩全息再现多层样本

doi:10.3969/j.issn.1000-1158.2017.06.06

Abstract
Figure/Table
References (15)
Related Citation (15)

Download: PDF (916 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract In order to study the reconstruction effect of three-layer samples using compressive holography, tomography experiment is proposed and compressive holography and traditional back-propagation digital holography is analyzed. The frequency domain sample reduction to make hologram sparse is used, remaining 25% data of the original hologram. Through the simulation experiment, that the correlation coefficient of the reconstructed image by compressive holography and simulation sample can reach 0.64. 4f optical system is introduced, and it separates three-layer samples apart with compressive holography method which can make reconstructed images much clearer and suppress background noise.

Key words： metrology in-line compressive holography 4f optical system tomography multilayer transparent samples three-layer sample reconstruction

Received: 14 December 2015 Published: 27 September 2017

PACS:

TB96

Fund:Research on GPS information ontology interoperability Methods

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	SUN Xi-kang
	YU Ying-jie
	WU Xiao-yan
	ZHOU Wen-jing

Cite this article:

SUN Xi-kang,YU Ying-jie,WU Xiao-yan, et al. Reconstruction of Multilayer Samples by In-line Compressive Holography[J]. Acta Metrologica Sinica, 2017, 38(6): 686-689.

URL:

http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2017.06.06 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2017/V38/I6/686

［1］Donoho D L. Compressed Sensing［J］. IEEE Transactions on Information Theory, 2006, 52(4): 1289-1306.
［2］Emmanuel J, Candès M B W. An Introduction to Compressive Sampling［J］. Signal Processing Magazine, 2008, 25(2): 21-30.
［3］Candes E J, Romberg J, Tao T. Robust Uncertainty Principles: Exact Signal Reconstruction from Highly Incomplete Frequency Information［J］. IEEE Transactions on Information Theory, 2004, 52(2): 489-509.
［4］Brady D J, Choi K, Marks D L, et al. Compressive Holography［J］. Optics Express, 2009, 17(15): 13040-13049.
［5］Xiao X Y, Zhou W J, Yu Y J. Solving inverse problems for off-axis holography using Twist［J］. Proc of SPIE, 2013, 22(17): 19863-19876.
［6］Clemente P, Durán V, Tajahuerce E, et al. Compressive holography with a single-pixel detector［J］.Optics Letters, 2013,38(14):2524-2527.
［7］Harn J, Lim S, Choi K, et al. Video-rate compressive holographic microscopic tomography［J］. Optics Express, 2011, 19(8):7289-7298.
［8］Williams L, Nehmetallah G, Banerjee P P. Digital tomographic compressive holographic reconstruction of three-dimensional objects in transmissive and reflective geometries［J］. Applied Optics, 2013, 52(8):1702-1710.
［9］Remacha C, Nickerson B S, Kreuzer H J. Tomography by point source digital holographic microscopy［J］. Applied Optics, 2014,53(16): 3520-3527.
［10］Harn J, Lim S, Choi K, et al. Compressive Holographic Microscopy［J］. Optical Society of America, 2009,90:2880-2882.
［11］Xiao X Y, Yu Y J, Zhou W J, et al. 4f amplified in-line compressive holography［J］. Optics Express, 2014, 22(17): 19860-19872.
［12］Wu F, Wan Y H, Man T L, et al. Compressive holographic imaging by self-interference Digital holography［J］. Digital Holography and 3D Imaging, 2015, 70:22-25.
［13］Li J, Pan Y Y, Li J S, et al. Compressive holographic imaging based on single in-line hologram and superconducting nanowire single-photon detector［J］. Optics Communications, 2015, 355:326–330.
［14］Bioucas-Dias J M, Figueiredo M A T. A New TwIST:Two-step iterative shrinkage/thresholding algorithms for imaging restoration［J］. IEEE Transactions on Image Processing, 2007, 16(12):2992-3004.
［15］Wang Z, Bovik A C. A Universal Image Quality Index［J］. IEEE Signal Processing Letters, 2002, 9(3): 81-84.