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High dynamic range imaging with PERIODIC

Published: 28 March 2008 Publication History

Abstract

This paper presents an approach for improving the effective dynamic range of a novel array imaging systems by using multiple images of the same scene taken with different exposure times and gain values. In this approach, multiple images are fused into a single high dynamic range radiance map whose intensities are proportional to the true radiance values in the scene. We show that our approach can produce improved high dynamic range recovery performance.

References

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P. Debevec, and J. Malik, Recovering high dynamic range radiance maps from photographs. In Pro. of SIGGRAPH 97, Computer Graphics Proceedings, Annual Conference Series, pp. 369--378, 1997.
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J. A. Ferwerda, S. N. Pattanaik, P. Shirley, and D. P. Greenberg, A model of visual adaptation for realistic image synthesis, In Proc. of the 23rd annual conference on Computer graphics and interactive techniques, pp. 249--258, Aug. 1996.
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M. D. Grossberg, and Shree K. Nayar, High Dynamic Range from Multiple Images: Which Exposures to Combine? Workshop on Color and Photometric Methods in Computer Vision, ICCV 2003
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B. K. Gunturk, Y. Altunbasak, and R. M. Mersereau, Multi-frame information fusion for gray-scale and spatial enhancement of images, In Proc. IEEE Int. Conf. Image Processing, Barcelona, Spain, Sep. 2003.
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M. A. Robertson, S. Borman, and R. L. Stevenson, Dynamic range improvement through multiple exposures, in Proc. IEEE Int. Conf. Image Processing, Vol. 3, pp. 159--163, 1999.
[6]
http://www.its.bldrdoc.gov/fs-1037/dir-013/_1853.htm
[7]
http://www.cambridgeincolour.com/tutorials/dynamic-range.htm
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R. Barnard, B. Gray, J. van der Gracht, M. Mirotznik, S. Matthews, PERIODIC: state-of-the-art array imaging technology, in Proc. 2007 ACM Southeast Conference, Mar., 2007.
[9]
R. Barnard, V. P. Pauca, T. Torgersen, R. Plemmons, S. Prasad, J. van der Gracht, J. Nagy, J. Chung, G. Behrmann, S. Mathews, M. Mirotznik, High-Resolution Iris Image Reconstruction from Low-Resolution Imagery, in Proc. SPIE, Advanced Signal Processing Algorithms, Architectures, and Implementations XVI, Vol. 6313, pp. D1-D13, San Diego, CA, Aug. 2006.

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cover image ACM Other conferences
ACMSE '08: Proceedings of the 46th annual ACM Southeast Conference
March 2008
548 pages
ISBN:9781605581057
DOI:10.1145/1593105
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 March 2008

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Author Tags

  1. computational imaging systems
  2. dynamic range
  3. dynamic range extension

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  • Research-article

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ACM SE08
ACM SE08: ACM Southeast Regional Conference
March 28 - 29, 2008
Alabama, Auburn

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Overall Acceptance Rate 502 of 1,023 submissions, 49%

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