skip to main content
10.1145/1576246.1531402acmconferencesArticle/Chapter ViewAbstractPublication PagessiggraphConference Proceedingsconference-collections
research-article

Dark flash photography

Published: 27 July 2009 Publication History

Abstract

Camera flashes produce intrusive bursts of light that disturb or dazzle. We present a prototype camera and flash that uses infra-red and ultra-violet light mostly outside the visible range to capture pictures in low-light conditions. This "dark" flash is at least two orders of magnitude dimmer than conventional flashes for a comparable exposure. Building on ideas from flash/no-flash photography, we capture a pair of images, one using the dark flash, other using the dim ambient illumination alone. We then exploit the correlations between images recorded at different wavelengths to denoise the ambient image and restore fine details to give a high quality result, even in very weak illumination. The processing techniques can also be used to denoise images captured with conventional cameras.

Supplementary Material

JPG File (tps009_09.jpg)
MP4 File (tps009_09.mp4)

References

[1]
Agrawal, A., Raskar, R., Nayar, S., and Li, Y. 2005. Removing photography artifacts using gradient projection and flash-exposure sampling. In ACM Transactions on Graphics (Proc. SIGGRAPH), vol. 24, 828--835.
[2]
Aharon, M., Elad, M., and Bruckstein, A. 2006. The KSVD: An algorithm for designing of overcomplete dictionaries for sparse representation. IEEE Trans. Signal Processing 54, 11 (November), 4311--4322.
[3]
Baker, S., Gross, R., and Matthews, I. 2004. Lucas-kanade 20 years on: A unifying framework. International Journal of Computer Vision 56, 221--255.
[4]
Bennett, E., Mason, J., and McMillan, L. 2007. Multispectral bilateral video fusion. IEEE Trans. Image Processing 16, 5, 1185--1194.
[5]
Chakrabarti, A., Hirakawa, K., and Zickler, T. 2008. Color constancy beyond bags of pixels. In CVPR, 1--6.
[6]
Christian, J., and Zapata, F., 2008. Noise Ninja, Photoshop denoising plugin. http://www.picturecode.com/.
[7]
Debevec, P. E., and Malik, J. 1997. Recovering high dynamic range radiance maps from photographs. ACM Transactions on Graphics (Proc. SIGGRAPH) 31, 3, 369--378.
[8]
Eisemann, E., and Durand, F. 2004. Flash photography enhancement via intrinsic relighting. In ACM Transactions on Graphics (Proc. SIGGRAPH), vol. 23, 673--678.
[9]
Farbman, Z., Fattal, R., Lischinski, D., and Szeliski, R. 2008. Edge-preserving decompositions for multi-scale tone and detail manipulation. In ACM Transactions on Graphics (Proc. SIGGRAPH), vol. 27, 671--680.
[10]
Fergus, R., Singh, B., Hertzmann, A., Roweis, S. T., and Freeman, W. 2006. Removing camera shake from a single photograph. ACM Transactions on Graphics (Proc. SIGGRAPH) 25, 787--794.
[11]
Jiaya, J. 2007. Single image motion deblurring using transparency. In CVPR, 1--8.
[12]
Levin, A., and Weiss, Y. 2007. User assisted separation of reflections from a single image using a sparsity prior. IEEE Trans. Pattern Analysis and Machine Intelligence 29, 9 (Sept), 1647--1654.
[13]
Levin, A., Fergus, R., Durand, F., and Freeman, W. 2007. Image and depth from a conventional camera with a coded aperture. ACM Transactions on Graphics (Proc. SIGGRAPH) 26, 3, 70.
[14]
McAuley, J. J., Caetano, T. S., Smola, A. J., and Franz, M. O. 2006. Learning high-order MRF priors of color images. In ICML '06, 617--624.
[15]
Mohan, A., Raskar, R., and Tumblin, J. 2008. Agile spectrum imaging: Programmable wavelength modulation for cameras and projectors. Computer Graphics Forum 27, 2, 709--717.
[16]
Morris, N., Avidan, S., Matusik, W., and Pfister, H. 2007. Statistics of infrared images. In CVPR, 1--7.
[17]
Park, J., Lee, M., Grossberg, M. D., and Nayar, S. K. 2007. Multispectral Imaging Using Multiplexed Illumination. In ICCV, 1--8.
[18]
Petschnigg, G., Agrawala, M., Hoppe, H., Szeliski, R., Cohen, M., and Toyama, K. 2004. Digital photography with flash and no-flash image pairs. ACM Transactions on Graphics (Proc. SIGGRAPH) 23, 3, 664--672.
[19]
Portilla, J., Strela, V., Wainwright, M. J., and Simoncelli, E. P. 2003. Image denoising using a scale mixture of Gaussians in the wavelet domain. IEEE Trans. Image Processing 12, 11 (November), 1338--1351.
[20]
Rorslett, B., 2008. http://www.naturfotograf.com/UV\_flowers_list.html.
[21]
Roth, S., and Black, M. J. 2005. Fields of Experts: A Framework for Learning Image Priors. In CVPR, vol. 2, 860--867.
[22]
Singh, B., Freeman, W. T., and Brainard, D. H. 2003. Exploiting spatial and spectral image regularities for color constancy. In Workshop on Statistical and Computational Theories of Vision.
[23]
Telleen, J., Sullivan, A., Yee, J., Wang, O., Gunawardane, P., Collins, I., and Davis, J. 2007. Synthetic shutter speed imaging. Computer Graphics Forum 26, 3 (Sept.), 591--598.
[24]
TLVs. 2001. TLVs and BEIs: threshold limit values for chemical substances and physical agents. American Conference of Governmental Industrial Hygienists.
[25]
Tomasi, C., and Manduchi, R. 1998. Bilateral filtering for gray and color images. In ICCV, 839--846.
[26]
Vos, J. 1978. Colorimetric and photometric properties of a 2-deg fundamental observer. Color Research and Application, 125--128.
[27]
Wandell, B. A. 1995. Foundations of Vision. Sinauer Associates.
[28]
Wang, O., Davis, J., Chuang, E., Rickard, I. and de Mesa, K., and Chirag, D. 2008. Video relighting using infrared illumination. Computer Graphics Forum 27.
[29]
Wang, Y., Yang, J., Yin, W., and Zhang, Y. 2008. A new alternating minimization algorithm for total variation image reconstruction. SIAM J. Imaging Sciences 1, 3, 248--272.
[30]
Yuan, L., Sun, J., Quan, L., and Shum, H.-Y. 2007. Image deblurring with blurred/noisy image pairs. In ACM Transactions on Graphics (Proc. SIGGRAPH), vol. 26, 1--10.

Cited By

View all
  • (2024)RFFNet: Towards Robust and Flexible Fusion for Low-Light Image DenoisingProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3680675(836-845)Online publication date: 28-Oct-2024
  • (2023)Purifying Low-Light Images via Near-Infrared Enlightened ImageIEEE Transactions on Multimedia10.1109/TMM.2022.323220625(8006-8019)Online publication date: 2023
  • (2021)Dense Cross-Modal Correspondence Estimation With the Deep Self-Correlation DescriptorIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2020.296552843:7(2345-2359)Online publication date: 1-Jul-2021
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
SIGGRAPH '09: ACM SIGGRAPH 2009 papers
July 2009
795 pages
ISBN:9781605587264
DOI:10.1145/1576246
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]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 July 2009

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. computational photography
  2. dark flash
  3. multi-spectral imaging
  4. spectral image correlations

Qualifiers

  • Research-article

Conference

SIGGRAPH09
Sponsor:

Acceptance Rates

SIGGRAPH '09 Paper Acceptance Rate 78 of 439 submissions, 18%;
Overall Acceptance Rate 1,822 of 8,601 submissions, 21%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 05 Mar 2025

Other Metrics

Citations

Cited By

View all
  • (2024)RFFNet: Towards Robust and Flexible Fusion for Low-Light Image DenoisingProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3680675(836-845)Online publication date: 28-Oct-2024
  • (2023)Purifying Low-Light Images via Near-Infrared Enlightened ImageIEEE Transactions on Multimedia10.1109/TMM.2022.323220625(8006-8019)Online publication date: 2023
  • (2021)Dense Cross-Modal Correspondence Estimation With the Deep Self-Correlation DescriptorIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2020.296552843:7(2345-2359)Online publication date: 1-Jul-2021
  • (2020)Adaptive Quantile Sparse Image (AQuaSI) Prior for Inverse Imaging ProblemsIEEE Transactions on Computational Imaging10.1109/TCI.2019.29568886(503-517)Online publication date: 2020
  • (2019)A Customized Camera Imaging Pipeline for Dermatological Imaging2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)10.1109/CVPRW.2019.00329(2711-2719)Online publication date: Jun-2019
  • (2018)Infrared image super-resolution using auxiliary convolutional neural network and visible image under low-light conditionsJournal of Visual Communication and Image Representation10.1016/j.jvcir.2018.01.01851(191-200)Online publication date: Feb-2018
  • (2017)Convolutional neural network-based infrared image super resolution under low light environment2017 25th European Signal Processing Conference (EUSIPCO)10.23919/EUSIPCO.2017.8081318(803-807)Online publication date: Aug-2017
  • (2017)DASC: Robust Dense Descriptor for Multi-Modal and Multi-Spectral Correspondence EstimationIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2016.261561939:9(1712-1729)Online publication date: 1-Sep-2017
  • (2017)Visibility enhancement of fluorescent substance under ambient illumination using flash photography2017 IEEE International Conference on Image Processing (ICIP)10.1109/ICIP.2017.8296556(1622-1626)Online publication date: Sep-2017
  • (2017)Catadioptric HyperSpectral Light Field Imaging2017 IEEE International Conference on Computer Vision (ICCV)10.1109/ICCV.2017.112(985-993)Online publication date: Oct-2017
  • Show More Cited By

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media