skip to main content
research-article

Linear Volumetric Focus for Light Field Cameras

Published:02 March 2015Publication History
Skip Abstract Section

Abstract

We demonstrate that the redundant information in light field imagery allows volumetric focus, an improvement of signal quality that maintains focus over a controllable range of depths. To do this, we derive the frequency-domain region of support of the light field, finding it to be the 4D hyperfan at the intersection of a dual fan and a hypercone, and design a filter with correspondingly shaped passband. Drawing examples from the Stanford Light Field Archive and images captured using a commercially available lenslet-based plenoptic camera, we demonstrate that the hyperfan outperforms competing methods including planar focus, fan-shaped antialiasing, and nonlinear image and video denoising techniques. We show the hyperfan preserves depth of field, making it a single-step all-in-focus denoising filter suitable for general-purpose light field rendering. We include results for different noise types and levels, through murky water and particulate matter, in real-world scenarios, and evaluated using a variety of metrics. We show that the hyperfan's performance scales with aperture count, and demonstrate the inclusion of aliased components for high-quality rendering.

Skip Supplemental Material Section

Supplemental Material

a15.mp4

mp4

70.6 MB

References

  1. E. H. Adelson and J. Y. A. WANG. 2002. Single lens stereo with a plenoptic camera. IEEE Trans. Pattern Anal. Mach. Intell. 14, 2, 99--106. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. A. Agrawal, Y. Xu, and R. Raskar. 2009. Invertible motion blur in video. ACM Trans. Graph. 28, 3. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. M. Aharon, M. Elad, and A. Bruckstein. 2006. K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation. IEEE Trans. Signal Process. 54, 11, 4311--4322. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. R. Ansari. 1987. Efficient IIR and FIR fan filters. IEEE Trans. Circ. Syst. 34, 8, 941--945.Google ScholarGoogle ScholarCross RefCross Ref
  5. J. Berent and P. L. Dragotti. 2007. Plenoptic manifolds. Signal Process. Mag. 24, 6, 34--44.Google ScholarGoogle ScholarCross RefCross Ref
  6. T. E. Bishop and P. Favaro. 2012. The light field camera: Extended depth of field, aliasing, and superresolution. IEEE Trans. Pattern Anal. Mach. Intell. 34, 5, 972--986. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. K. Bitsakos and C. Fermuller. 2006. Depth estimation using the compound eye of dipteran flies. Biol. Cybernet. 95, 5, 487--501. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. R. Bolles, H. Baker, and D. Marimont. 1987. Epipolar-plane image analysis: An approach to determining structure from motion. Intl. J. Comput. Vis. 1, 1, 7--55.Google ScholarGoogle ScholarCross RefCross Ref
  9. A. Buades, B. Coll, and J.-M. Morel. 2005. A review of image denoising algorithms, with a new one. SIAM J. Multiscale Model. Simul. 4, 2, 490--530.Google ScholarGoogle ScholarCross RefCross Ref
  10. A. Cetin, O. Gerek, and Y. Yardimci. 1997. Equiripple FIR filter design by the FFT algorithm. IEEE Signal Process. Mag. 14, 2, 60--64.Google ScholarGoogle ScholarCross RefCross Ref
  11. J. Chai, X. Tong, S. Chan, and H. Shum. 2000. Plenoptic sampling. In Proceedings of the 27th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH'00). 307--318. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. S.-C. Chan and H.-Y. Shum. 2000. A spectral analysis for light field rendering. In Proceedings of the International Conference on Image Processing (ICIP'00). Vol. 2, 25--28.Google ScholarGoogle ScholarCross RefCross Ref
  13. O. Cossairt, M. Gupta, and S. Nayar. 2012. When does computational imaging improve performance? IEEE Trans. Image Process. 22, 2, 447--458. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. K. Dabov, A. Foi, and K. Egiazarian. 2007. Video denoising by sparse 3D transform-domain collaborative filtering. In Proceedings of the 15th European Signal Processing Conference (EURIPCO'07). 7.Google ScholarGoogle Scholar
  15. K. J. Dana, B. Van Ginneken, S. K. Nayar, and J. J. Koenderink. 1999. Reflectance and texture of real-world surfaces. ACM Trans. Graph. 18, 1, 1--34. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. D. G. Dansereau. 2003. 4D light field processing and its application to computer vision. M.S. thesis, Department of Electrical and Computer Engineering, University of Calgary. http://www-personal.acfr.usyd.edu.au/ddan1654/dansereau2003MscThesis.pdf.Google ScholarGoogle Scholar
  17. D. G. Dansereau. 2014. Plenoptic signal processing for robust vision in field robotics. Ph.D. thesis, Australian Centre for Field Robotics, School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney.Google ScholarGoogle Scholar
  18. D. G. Dansereau, D. L. Bongiorno, O. Pizarro, and S. B. Williams. 2013a. Light field image denoising using a linear 4D frequency-hyperfan all-in-focus filter. In Proceedings of the SPIE Conference on Computational Imaging (SPIE'13). Vol. 8657.Google ScholarGoogle Scholar
  19. D. G. Dansereau, O. Pizarro, and S. B. Williams. 2013b. Decoding, calibration and rectification for lenselet-based plenoptic cameras. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR'13). 1027--1034. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. D. G. Dansereau and L. T. Bruton. 2003. A 4D frequency-planar IIR filter and its application to light field processing. In Proceedings of the International Symposium on Circuits and Systems (ISCAS'03). Vol. 4. 476--479.Google ScholarGoogle Scholar
  21. D. G. Dansereau and L. T. Bruton. 2004. Gradient-based depth estimation from 4D light fields. In Proceedings of the International Symposium on Circuits and Systems (ISCAS'04). Vol. 3, 549--552.Google ScholarGoogle Scholar
  22. D. G. Dansereau and L. T. Bruton. 2007. A 4-D dual-fan filter bank for depth filtering in light fields. IEEE Trans. Signal Process. 55, 2, 542--549. Google ScholarGoogle ScholarCross RefCross Ref
  23. D. G. Dansereau, I. Mahon, O. Pizarro, and S. B. Williams. 2011. Plenoptic flow: Closed-form visual odometry for light field cameras. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'11). 4455--4462.Google ScholarGoogle Scholar
  24. D. G. Dansereau and S. B. Williams. 2011. Seabed modeling and distractor extraction for mobile AUVS using light field filtering. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA'11). 1634--1639.Google ScholarGoogle Scholar
  25. F. Durand, N. Holzschuch, C. Soler, E. Chan, and F. Sillion. 2005. A frequency analysis of light transport. In Proceedings of the 32nd International Conference on Computer Graphics and Interactive Techniques: Papers (SIGGRAPH'05). 1115--1126. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. M. Elad and M. Aharon. 2006. Image denoising via sparse and redundant representations over learned dictionaries. IEEE Trans. Image Process. 15, 12, 3736--3745. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. W. Freeman, A. Levin, S. Hasinoff, P. Green, and F. Durand. 2009. 4D frequency analysis of computational cameras for depth of field extension. Tech. rep. MIT-CSAIL-TR-2009-019. http://dspace.mit.edu/handle/1721.1/45513.Google ScholarGoogle Scholar
  28. W. S. Geisler. 2008. Visual perception and the statistical properties of natural scenes. Ann. Rev. Psychol. 59, 167--192.Google ScholarGoogle ScholarCross RefCross Ref
  29. B. Goldluecke and S. Wanner. 2013. The variational structure of disparity and regularization of 4D light fields. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR'13). 1003--1010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. X. Gu, S. J. Gortler, and M. F. Cohen. 1997. Polyhedral geometry and the two-plane parameterization. In Proceedings of the Eurographics Workshop on Rendering Techniques. Springer, 1--12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. O. G. Guleryuz. 2007. Weighted averaging for denoising with overcomplete dictionaries. IEEE Trans. Image Process. 16, 12, 3020--3034. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. A. Isaksen, L. McMillan, and S. Gortler. 2000. Dynamically reparameterized light fields. In Proceedings of the International Conference on Computer Graphics and Interactive Techniques (SIGGRAPH'00). 297--306. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Y. Ji, J. Ye, and J. Yu. 2013. Reconstructing gas flows using light-path approximation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR'13). 2507--2514. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. J.-H. Lambert. 1760. Photometria, sive de Mensura et gradibus luminis, colorum et umbrae. Eberhard Klett.Google ScholarGoogle Scholar
  35. A. Levin and F. Durand. 2010. Linear view synthesis using a dimensionality gap light field prior. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR'10). 1831--1838.Google ScholarGoogle Scholar
  36. A. Levin, S. Hasinoff, P. Green, F. Durand, and W. Freeman. 2009. 4D frequency analysis of computational cameras for depth of field extension. ACM Trans. Graph. 28, 3. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. M. Levoy, B. Chen, V. Vaish, M. Horowitz, I. McDowall, and M. Bolas. 2004. Synthetic aperture confocal imaging. ACM Trans. Graph. 23, 3, 825--834. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. M. Levoy and P. Hanrahan. 1996. Light field rendering. In Proceedings of the International Conference on Computer Graphics and Interactive Techniques (SIGGRAPH'96). 31--42. Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. A. Lumsdaine and T. Georgiev. 2008. Full resolution lightfield rendering. Tech. rep., Adobe Systems. http://tgeorgiev.net/FullResolution.pdf.Google ScholarGoogle Scholar
  40. A. Lumsdaine and T. Georgiev. 2009. The focused plenoptic camera. In Proceedings of the IEEE International Conference on Computational Photography (ICCP'09). 1--8.Google ScholarGoogle Scholar
  41. K. Maeno, H. Nagahara, A. Shimada, and R.-I. Taniguchi. 2013. Light field distortion feature for transparent object recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR'13). 2786--2793. Google ScholarGoogle ScholarDigital LibraryDigital Library
  42. K. Mitra, O. Cossairt, and A. Veeraraghavan. 2013. A frame-work for the analysis of computational imaging systems with practical applications. http://arxiv.org/pdf/1308.1981.pdf.Google ScholarGoogle Scholar
  43. H. Nagahara, S. Kuthirummal, C. Zhou, and S. K. Nayar. 2008. Flexible depth of field photography. In Proceedings of the European Conference on Computer Vision (ECCV'08). Springer, 60--73. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. J. Neumann, C. Fermuller, Y. Aloimonos, and V. Brajovic. 2005. Compound eye sensor for 3D ego motion estimation. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'05). Vol. 4. 3712--3717.Google ScholarGoogle Scholar
  45. R. Ng. 2005. Fourier slice photography. ACM Trans. Graph. 24, 3, 735--744. Google ScholarGoogle ScholarDigital LibraryDigital Library
  46. R. Ng, M. Levoy, M. Bredif, G. Duval, M. Horowitz, and P. Hanrahan. 2005. Light field photography with a hand-held plenoptic camera. Tech. rep. CSTR 2, Department of Computer Science, Stanford University. https://graphics.stanford.edu/papers/lfcamera/lfcamera-150dpi.pdf.Google ScholarGoogle Scholar
  47. M. O'TOOLE, R. Raskar, and K. N. Kutulakos. 2012. Primal-dual coding to probe light transport. In Proceedings of the International Conference on Computer Graphics and Interactive Techniques (SIGGRAPH'12). Vol. 31. 39. Google ScholarGoogle ScholarDigital LibraryDigital Library
  48. J. G. Proakis and M. Salehi. 2007. Digital Communications 5th Ed. McGraw-Hill.Google ScholarGoogle Scholar
  49. L. R. Rabiner and B. Gold. 1975. Theory and Application of Digital Signal Processing, Volume 1. Prentice-Hall.Google ScholarGoogle Scholar
  50. R. Raskar, A. Agrawal, and J. Tumblin. 2006. Coded exposure photography: Motion deblurring using fluttered shutter. ACM Trans. Graph. 25, 3, 795--804. Google ScholarGoogle ScholarDigital LibraryDigital Library
  51. R. Raskar, A. Agrawal, C. A. Wilson, and A. Veeraraghavan. 2008. Glare aware photography: 4D ray sampling for reducing glare effects of camera lenses. ACM Trans. Graph. 27, 3. Google ScholarGoogle ScholarDigital LibraryDigital Library
  52. D. L. Ruderman. 1997. Origins of scaling in natural images. Vis. Res. 37, 23, 3385--3398.Google ScholarGoogle ScholarCross RefCross Ref
  53. A. Shnayderman, A. Gusev, and A. Eskicioglu. 2006. An SVD-based grayscale image quality measure for local and global assessment. IEEE Trans. Image Process. 15, 2, 422--429. Google ScholarGoogle ScholarDigital LibraryDigital Library
  54. J. Stewart, J. Yu, S. J. Gortler, and L. McMillan. 2003. A new reconstruction filter for undersampled light fields. In Proceedings of the 14th Eurographics Workshop on Rendering (EGRW'03). Eurographics Association, 150--156. Google ScholarGoogle ScholarDigital LibraryDigital Library
  55. V. Vaish, M. Levoy, R. Szeliski, C. Zitnick, and S. Kang. 2006. Reconstructing occluded surfaces using synthetic apertures: Stereo, focus and robust measures. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR'06). Vol. 2. 2331--2338. Google ScholarGoogle ScholarDigital LibraryDigital Library
  56. A. Veeraraghavan, R. Raskar, A. Agrawal, A. Mohan, and J. Tumblin. 2007. Dappled photography: Mask enhanced cameras for heterodyned light fields and coded aperture refocusing. ACM Trans. Graph. 26, 3. Google ScholarGoogle ScholarDigital LibraryDigital Library
  57. Z. Wang, A. Bovik, H. Sheikh, and E. Simoncelli. 2004. Image quality assessment: From error visibility to structural similarity. IEEE Trans. Image Process. 13, 4, 600--612. Google ScholarGoogle ScholarDigital LibraryDigital Library
  58. S. Wanner and B. Goldluecke. 2013. Variational light field analysis for disparity estimation and super-resolution. IEEE Trans. Pattern Anal. Mach. Intell. 36, 3, 606--619. Google ScholarGoogle ScholarDigital LibraryDigital Library
  59. B. Wilburn, N. Joshi, V. Vaish, E. Talvala, E. Antunez, A. Barth, A. Adams, M. Horowitz, and M. Levoy. 2005. High performance imaging using large camera arrays. ACM Trans. Graph. 24, 3, 765--776. Google ScholarGoogle ScholarDigital LibraryDigital Library
  60. H. Yang, M. Pollefeys, G. Welch, J. Frahm, and A. Ilie. 2007. Differential camera tracking through linearizing the local appearance manifold. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR'07). 1--8.Google ScholarGoogle Scholar
  61. Z. Yu, X. Guo, X. Chen, and Y. Yu. 2013. Catadioptric array photography for low light imaging. In Proceedings of the 2nd IEEE International Workshop on Computational Cameras and Displays (CCD'13).Google ScholarGoogle Scholar

Index Terms

  1. Linear Volumetric Focus for Light Field Cameras

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in

      Full Access

      • Published in

        cover image ACM Transactions on Graphics
        ACM Transactions on Graphics  Volume 34, Issue 2
        February 2015
        136 pages
        ISSN:0730-0301
        EISSN:1557-7368
        DOI:10.1145/2742222
        Issue’s Table of Contents

        Copyright © 2015 ACM

        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]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 2 March 2015
        • Accepted: 1 August 2014
        • Revised: 1 June 2014
        • Received: 1 March 2014
        Published in tog Volume 34, Issue 2

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article
        • Research
        • Refereed

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader