Skip to main content
SpringerLink
Log in

Prototype of Super-Resolution Camera Array System

  • Conference paper
  • First Online:
Advances in Visual Computing (ISVC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9474))

Included in the following conference series:

  • 2901 Accesses

Abstract

We present a prototype of a super-resolution camera array system. Since the proposed system consists of a number of low-cost camera devices, all of which operate synchronously, it is a low-cost, high quality imaging system, and capable of handling moving targets. However, when the targets are located near the system, parallax and differences in photographic conditions among the cameras become pronounced. In addition, conventional super-resolution techniques frequently emphasize noise, as well as edges, contours, and so on, when the number of the observed (i.e., low resolution) images is limited. Therefore, we also propose the following procedures for our camera-array system: (1) color calibration among cameras, (2) automated region of the interest (ROI) detection under large parallax, and (3) effective noise reduction with effective edge preservation. We developed a camera array system comprising 12 low-cost Web camera devices. We confirm that the proposed system in general reduces the drawbacks of the array system and achieves approximately a 2 dB higher S/N ratio, i.e., equivalent to the effect of two additional images.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Park, S.C., Park, M.K., Kang, M.G.: Super-resolution image reconstruction: a technical overview. IEEE Signal Process. Mag. 20, 21–36 (2003)

    Article  Google Scholar 

  2. Freeman, W.T., Jones, T.R., Pasztor, E.C.: Example-based super-resolution. IEEE Comput. Graphics Appl. 22, 56–65 (2002)

    Article  Google Scholar 

  3. Takashi, K., Takahiro, S.: Super-resolution decoding of the JPEG coded image data using total-variation regularization. In: Picture Coding Symposium, pp. 114–117 (2010)

    Google Scholar 

  4. Tom, B., Katsaggelos, A.: Reconstruction of a high-resolution image by simultaneous registration, restoration, and interpolation of low-resolution images. In: IEEE International Conference on Image Processing, vol. 2, pp. 539–542 (1995)

    Google Scholar 

  5. Schultz, R., Stevenson, R.: A bayesian approach to image expansion for improved definition. IEEE Trans. Image Process. 3, 233–242 (1994)

    Article  Google Scholar 

  6. Schultz, R., Stevenson, R.: Extraction of high-resolution frames from video sequences. IEEE Trans. Image Process. 5, 996–1011 (1996)

    Article  Google Scholar 

  7. Irani, M., Peleg, S.: Improving resolution by image registration. Graph. Models Image Process. 53, 231–239 (1991)

    Article  Google Scholar 

  8. Tsai, R., Huang, T.: Multiframe image restoration and registration. In: Advances in Computer Vision and Image, vol. 1, pp. 317–339 (1984)

    Google Scholar 

  9. Eren, P., Sezan, M., Tekalp, A.: Robust, object-based high resolution image reconstruction from low-resolution video. IEEE Trans. Image Process. 6, 1446–1451 (1997)

    Article  Google Scholar 

  10. Patti, A.J., Altunbasak, Y.: Artifact reduction for set theoretic super resolution image reconstruction with edge adaptive constraints and higher-order interpolants. IEEE Trans. Image Process. 10, 179–186 (2001)

    Article  Google Scholar 

  11. Zitova, B., Flusser, J.: Image registration methods: a survey. Image Vis. Comput. 21, 977–1000 (2003)

    Article  Google Scholar 

  12. Lowe, D.G.: Distinctive image features from scaleinva-invariant keypoints. Proc. Int. J. Comput. Vis. (IJCV) 60, 91–110 (2004)

    Article  Google Scholar 

  13. Bay, H., Ess, A., Tuytelaars, T., Gool, L.V.: Speeded-up robust features (surf). Comput. Vis. Image Underst. 110, 346–359 (2008)

    Article  Google Scholar 

  14. Tung, T., Nobuhara, S., Matsuyama, T.: Simultaneous super-resolution and 3d video using graph-cuts. In: IEEE Conference Computer Vision Pattern Recognition, Anchorage (2008)

    Google Scholar 

  15. Aghav, S., Kumar, A., Gadakar, G., Mehta, A., Mhaisane, A.: Mitigation of rotational constraints in image based plagiarism detection using perceptual hash. Int. J. Comput. Sci. Trends Technol. 2, 28–32 (2014)

    Google Scholar 

  16. Farsiu, S., Robinson, M.D., Elad, M., Milanfar, P.: Fast and robust multi-frame super-resolution. IEEE Trans. Image Process. 13, 1327–1344 (2004)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Applied Informatics, Graduate School of Science and Engineering, Hosei University, Tokyo, Japan

    Daiki Hirao & Hitoshi Iyatomi

Authors
  1. Daiki Hirao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hitoshi Iyatomi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hitoshi Iyatomi .

Editor information

Editors and Affiliations

  1. University of Nevada, Reno, Nevada, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, California, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, Nevada, USA

    Darko Koracin

  5. University of Houston, Houston, Texas, USA

    Ioannis Pavlidis

  6. IBM T.J. Watson Research Center, Yorktown Heights, New York, USA

    Rogerio Feris

  7. Purdue University, West Lafayette, Indiana, USA

    Tim McGraw

  8. Side Effects Software, Santa Monica, California, USA

    Mark Elendt

  9. The DiVE, Durham, North Carolina, USA

    Regis Kopper

  10. Texas A&M University, College Station, Texas, USA

    Eric Ragan

  11. Kent State University, Kent, Ohio, USA

    Zhao Ye

  12. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Gunther Weber

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Hirao, D., Iyatomi, H. (2015). Prototype of Super-Resolution Camera Array System. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2015. Lecture Notes in Computer Science(), vol 9474. Springer, Cham. https://doi.org/10.1007/978-3-319-27857-5_81

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-27857-5_81

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27856-8

  • Online ISBN: 978-3-319-27857-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation