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EURASIP Journal on Advances in Signal Processing
EURASIP Journal on Advances in Signal Processing Cover Image
  • Research Article
  • Open Access

Design of Large Field-of-View High-Resolution Miniaturized Imaging System

EURASIP Journal on Advances in Signal Processing20072007:059546

https://doi.org/10.1155/2007/59546

©  N. A. Ahuja and N. K. Bose. 2007

  • Received: 29 September 2006
  • Accepted: 16 April 2007
  • Published:

Abstract

Steps are taken to design the optical system of lenslet array/photoreceptor array plexus on curved surfaces to achieve a large field of view (FOV) with each lenslet capturing a portion of the scene. An optimal sampling rate in the image plane, as determined by the pixel pitch, is found by the use of an information theoretic performance measure. Since this rate turns out to be sub-Nyquist, superresolution techniques can be applied to the multiple low-resolution (LR) images captured on the photoreceptor array to yield a single high-resolution (HR) image of an object of interest. Thus, the computational imaging system proposed is capable of realizing both the specified resolution and specified FOV.

Keywords

  • Information Technology
  • Sampling Rate
  • Image System
  • Optical System
  • Image Plane

Authors’ Affiliations

(1)
Department of Electrical Engineering, Spatial and Temporal Signal Processing Center, The Pennsylvania State University, University Park, PA 16802, USA

References

  1. Dowski ER Jr., Cathey WT: Extended depth of field through wave-front coding. Applied Optics 1995,34(11):1859-1866. 10.1364/AO.34.001859View ArticleGoogle Scholar
  2. Adelson EH, Wang JYA: Single lens stereo with a plenoptic camera. IEEE Transactions on Pattern Analysis and Machine Intelligence 1992,14(2):99-106. 10.1109/34.121783View ArticleGoogle Scholar
  3. Ng R, Levoy M, Brédif M, Duval G, Horowitz M, Hanrahan P: Light field photography with a hand-held plenoptic camera. In Tech. Rep. CTSR 2005-02. Stanford University, Stanford, Calif, USA; 2005. https://doi.org/graphics.stanford.edu/papers/lfcamera/lfcamera-150dpi.pdfGoogle Scholar
  4. Nayar SK: Catadioptric omnidirectional camera. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June 1997, San Juan, Puerto Rico, USA 482–488.View ArticleGoogle Scholar
  5. Kang MG, Chaudhuri S (Eds): Super-resolution image reconstruction In IEEE Signal Processing Magazine 2003,20(3):19-20. 10.1109/MSP.2003.1203206Google Scholar
  6. Bose NK, Ahuja NA: Superresolution and noise filtering using moving least squares. IEEE Transactions on Image Processing 2006,15(8):2239-2248.View ArticleGoogle Scholar
  7. Bose NK, Chan RH, Ng MK (Eds): High-resolution image reconstruction—I In International Journal of Imaging Systems and Technology 2004,14(2):35-89. 10.1002/ima.20005Google Scholar
  8. Bose NK, Chan RH, Ng MK (Eds): High-resolution image reconstruction—II In International Journal of Imaging Systems and Technology 2004,14(3):91-145. 10.1002/ima.20012Google Scholar
  9. Huck FO, Fales CL, Alter-Gartenberg R, Park SK, Rahman Z: Information-theoretic assessment of sampled imaging systems. Optical Engineering 1999,38(5):742-762. 10.1117/1.602264View ArticleGoogle Scholar
  10. Kitamura Y, Shogenji R, Yamada K, et al.: Reconstruction of a high-resolution image on a compound-eye image-capturing system. Applied Optics 2004,43(8):1719-1727. 10.1364/AO.43.001719View ArticleGoogle Scholar
  11. Duparré J, Dannberg P, Schreiber P, Bräuer A, Tünnermann A: Artificial apposition compound eye fabricated by micro-optics technology. Applied Optics 2004,43(22):4303-4310. 10.1364/AO.43.004303View ArticleGoogle Scholar
  12. Lohmann AW: Scaling laws for lens systems. Applied Optics 1989,28(23):4996-4998. 10.1364/AO.28.004996View ArticleGoogle Scholar
  13. Born M, Wolf E: Principles of Optics: Electromagnetic Theory of Propogation, Interference and Diffraction of Light. Pergamon Press, Oxford, UK; 1980.Google Scholar
  14. Hecht E: Optics. Addison Wesley, New York, NY, USA; 1998.Google Scholar
  15. Goodman JW: Introduction to Fourier Optics. 2nd edition. McGraw-Hill, New York, NY, USA; 1996.Google Scholar
  16. Fossum ER: Digital camera system on a chip. IEEE Micro 1998,18(3):8-15. 10.1109/40.683047View ArticleGoogle Scholar
  17. Nakamura J: Basics of image sensors. In Image Sensors and Signal Processing for Digital Still Cameras. Edited by: Nakamura J. Taylor and Francis, London, UK; 2006:53-64.Google Scholar
  18. El Gamal A, Eltoukhy H: CMOS image sensors. IEEE Circuits and Devices Magazine 2005,21(3):6-20. 10.1109/MCD.2005.1438751View ArticleGoogle Scholar
  19. McCluney R: Introduction to Radiometry and Photometry. Artech House, Boston, Mass, USA; 1994.Google Scholar
  20. Papoulis A: Probability, Random Variables and Stochastic Processes. 3rd edition. McGraw-Hill, New York, NY, USA; 1991.MATHGoogle Scholar

Copyright

© N. A. Ahuja and N. K. Bose. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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