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Super-resolution reconstruction in a computational compound-eye imaging system

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Abstract

From consumer electronics to biomedical applications, device miniaturization has shown to be highly desirable. This often includes reducing the size of some optical systems. However, diffraction effects impose a constraint on image quality when we simply scale down the imaging parameters. Over the past few years, compound-eye imaging system has emerged as a promising architecture in the development of compact visual systems. Because multiple low-resolution (LR) sub-images are captured, post-processing algorithms for the reconstruction of a high-resolution (HR) final image from the LR images play a critical role in affecting the image quality. In this paper, we describe and investigate the performance of a compound-eye system recently reported in the literature. We discuss both the physical construction and the mathematical model of the imaging components, followed by an application of our super-resolution algorithm in reconstructing the image. We then explore several variations of the imaging system, such as the incorporation of a phase mask in extending the depth of field, which are not possible with a traditional camera. Simulations with a versatile virtual camera system that we have built verify the feasibility of these additions, and we also report the tolerance of the compound-eye system to variations in physical parameters, such as optical aberrations, that are inevitable in actual systems.

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References

  • Bose N.K., Boo K.J. (1998). High-resolution image reconstruction with multisensors. International Journal of Imaging Systems and Technology 9(4): 294–304

    Article  Google Scholar 

  • Castleman K.R. (1996). Digital image processing. Prentice Hall, Englewood Cliffs, NJ

    Google Scholar 

  • Castro A., Ojeda-Castañeda J. (2004). Asymmetric phase masks for extended depth of field. Applied Optics 43(17): 3474–3479

    Article  Google Scholar 

  • Dowski E.R. Jr., Cathey W.T. (1994). Single-lens single-image incoherent passive-ranging systems. Applied Optics 33(29): 6762–6773

    Article  Google Scholar 

  • Dowski E.R. Jr., Cathey W.T. (1995). Extended depth of field through wave-front coding. Applied Optics 34(11): 1859–1866

    Google Scholar 

  • Duparré J., Dannberg P., Schreiber P., Bräuer A., Tünnermann A. (2005). Thin compound eye camera. Applied Optics 44(15): 2949–2956

    Article  Google Scholar 

  • Duparré, J., Schreiber, P., Dannberg, P., Scharf, T., Pelli, P., Völkel, R., Herzig, H.-P., & Bräuer, A. (2004). Artificial compound eyes—different concepts and their application to ultra flat image acquisition sensors. In: MOEMS and miniaturized systems IV, ser. proceedings of the SPIE, San Jose, California, USA, Vol. 5346, pp. 89–100.

  • Duparré J., Schreiber P., Matthes A., Pshenay-Severin E., Bräuer A., Tünnermann A. (2005). Microoptical telescope compound eye. Optics Express 13(3): 889–903

    Article  Google Scholar 

  • Elad M., Feuer A. (1997). Restoration of a single superresolution image from several blurred, noisy, and undersampled measured images. IEEE Transactions on Image Processing 6(12): 1646–1658

    Article  Google Scholar 

  • Goodman J.W. (1996). Introduction to fourier optics. 2nd ed. McGraw-Hill, New York

    Google Scholar 

  • Hornsey, R., Thomas, P., Wong, W., Pepic, S., Yip, K., & Krishnasamy, R. (2004). Electronic compound-eye image sensor: Construction and calibration. In: Proceedings of the IS&T/SPIE symposium on electronic imaging 2004. Niagara Falls, Ontario, Candada.

  • Katsaggelos A.K. (1991). Digital image restoration. Springer, New York

    Google Scholar 

  • Kitamura Y., Showgenji R., Yamada K., Miyatake S., Miyamoto M. Morimoto, T., Masaki, Y., Kondou, N., Miyazaki, D., & Tanida, J. (2004). Reconstruction of a high-resoloution image on a compound-eye image-capturing system. Applied Optics, 43(8), 1719–1727.

    Google Scholar 

  • Krishnasamy, R., Wong, W., Shen, E., Pepic, S., Hornsey, R., & Thomas, P. (2004). High precision target tracking with a compound-eye image sensor. In: Canadian conference on electrical and computer engineering 2004, San Jose, California, USA.

  • Lam E.Y. (2002). Digital restoration of defocused images in the wavelet domain. Applied Optics 41(23): 4806–4811

    Google Scholar 

  • Lam E.Y., Goodman J.W. (1998). Discrete cosine transform domain restoration of defocused images. Applied Optics 37(26): 6213–6218

    Article  Google Scholar 

  • Mait J.N., Athale R., van der Gracht J. (2003). Evolutionary paths in imaging and recent trends. Optics Express 11(18): 2093–2101

    Article  Google Scholar 

  • Neumann, J., Fermüller, C., Aloimonos, Y., & Brajovic, V. (2004). Compound eye sensor for 3D ego motion estimation. In: Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS ’04), IEEE.

  • Ng M., Bose N.K. (2002). Analysis of displacement errors in high-resolution image reconstruction with multisensors. IEEE Transactions on Circuits and Systems I 49, 806–813

    Article  Google Scholar 

  • Ng M.K., Bose N.K. (2003). Mathematical analysis of super-resolution methodology. IEEE Signal Processing Magazine 20(3): 62–74

    Article  Google Scholar 

  • Ng M.K., Chan R.H., Chan T.F., Yip A.M. (2000). Cosine transform preconditioners for high resolution image reconstruction. Linear Algebra and Its Applications 316(1–3): 89–104

    Article  MATH  MathSciNet  Google Scholar 

  • Ng M., Yip A. (2001). A fast MAP algorithm for high-resolution image reconstruction with multisensors. Multidimensional Systems and Signal Processing 12(2): 143–164

    Article  MATH  MathSciNet  Google Scholar 

  • Prasad S., Torgersen T., Pauca P., Plemmons R., van der Gracht J. (2004). High-resolution imaging using integrated optical systems. International Journal on Imaging Systems and Technology 14(2): 67–74

    Article  Google Scholar 

  • Sherif S.S., Cathey W.T., Dowski E.R. (2004). Phase plate to extend the depth of field of incoherent hybrid imaging systems. Applied Optics 43(13): 2709–2721

    Article  Google Scholar 

  • Tanida J., Kumagai T., Yamada K., Miyatake S., Ishida K., Morimoto T., Kondou N., Miyazaki D., Ichioka Y. (2001). Thin observation module by bound optics (TOMBO): Concept and experimental verification. Applied Optics 40(11): 1806–1813

    Google Scholar 

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Correspondence to Edmund Y. Lam.

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Chan, WS., Lam, E.Y., Ng, M.K. et al. Super-resolution reconstruction in a computational compound-eye imaging system. Multidim Syst Sign Process 18, 83–101 (2007). https://doi.org/10.1007/s11045-007-0022-3

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  • DOI: https://doi.org/10.1007/s11045-007-0022-3

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