Compact Compound Imaging System with Large Target Surface

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Abstract:

Compact compound imaging system with large CCD target surface has been researched. The target surface reaches 50mmX50mm, and reduces the system processing and installation difficulty. We present the system overall plan and discuss the imaging characteristics. The imaging results for sector resolution target show that the system can image with multi channel crosstalk free. The results show that whether the single convex lens system or double convex lens system, the definition and contrast of single channel graphs are poor. However we can get the super resolution image by POCS algorithm. The reconstructed results show that image quality has been obviously improved compared with the single channel image, which proof the availability of the compact compound imaging system with large CCD target surface. Key words: Compact ompound imaging system, Microlens array, Doublet lens, POCS

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Key Engineering Materials (Volumes 609-610)

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863-866

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April 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Tanida J, Kumagai T, Yamada K, et a1. Thin observation module by bound optics (T0MBO: concept and experimental verification [J]. Appl. Opt., 2001, 40(10): 1806—1813.

DOI: 10.1364/ao.40.001806

Google Scholar

[2] Mohan Shankar, Rebecca Willett, Thin infrared imaging systems through multichannel sampling [J]. Appl. Opt., 2007, 47(10): 1756—1761.

Google Scholar

[3] N.P. Pitsianis D.J. Brady,A. Portnoy,X. Sun,T. Suleski, et al. Compressive imaging sensors[C], Proc. SPIE 6232, Intelligent Integrated Microsystems, 2006: 62320—62326.

DOI: 10.1117/12.666451

Google Scholar

[4] Predrag Milojkovic, John Gill, Daniel Frattin, Kevin Coyle, Karl Haack, et al. Multichannel, agile, computationally enhanced camera based on the PANOPTES architecture[C] , Proc. SPIE 7692, Unmanned Systems Technology XII, 2010: 76921—76928.

DOI: 10.1117/12.864995

Google Scholar

[5] TAN Xue-chun, WU Zhi-chao, LIANG Zhu. Design and experiment of artificial compound eye receiving system[J]. Optics and Precision Engineering, 19(5),2011 : 992~997 (in Chinese).

DOI: 10.3788/ope.20111905.0992

Google Scholar

[6] GUO Fang, WANG Ke-yi, YAN Pei-zheng, WU Qing-lin. Calibration of compound eye system for target positioning with large field of view[J]. Optics and Precision Engineering, 2012, 20(5): 913~920 (in Chinese).

DOI: 10.3788/ope.20122005.0913

Google Scholar

[7] K. Nitta, R. Shogenji, S. Miyatake, and J. Tanida, Image reconstruction for thin observation module by bound optics by using the iterative backprojection method [J], Appl. Opt. 45(8), 2006: 2893–2900.

DOI: 10.1364/ao.45.002893

Google Scholar

[8] H. -B. Lan S.L. Wood M.P. Christensen, and D. Rajan, Benefits of optical system diversity for multiplexed image reconstruction[J] , Appl. Opt. 45(8), 2006: 2859–2870.

DOI: 10.1364/ao.45.002859

Google Scholar

[9] Kenneth R. Castleman , Digital Image Processing[M], Pearson Education, (2003).

Google Scholar

[10] Shachar Mendelowitz, Iftach Klapp, and David Mendlovic, Design of an image restoration algorithm for the TOMBO imaging system[J], J. Opt. Soc. Am. A 30(4), 2013: 1193-1204.

DOI: 10.1364/josaa.30.001193

Google Scholar

[11] S.S. Panda1, M.S.R. S Prasad2 and Dr. G. Jena3, POCS Based Super-Resolution Image Reconstruction Using anAdaptive Regularization Parameter[J], International Journal of Computer Science Issues, 8(5), 2013: 528-612.

Google Scholar