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Accurate Depth-of-Field Rendering Using Adaptive Bilateral Depth Filtering

  • Shang Wu
  • Kai Yu
  • Bin Sheng
  • Feiyue Huang
  • Feng Gao
  • Lizhuang Ma
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7633)

Abstract

Real-time depth of field (DoF) rendering is crucial to realistic image synthesis and VR applications. This paper presents a new method to simulate the depth-of-field effects with bilateral depth filtering. Unlike the traditional rendering methods that handle the depth-of-field with Gaussian filtering, we develop a new DoF filter, called adaptive bilateral depth filter, to adaptively postfilter the pixels according to their depth variance. Depth information is used to focus on the objects with edge-preserving property. Our approach can eliminate the artifacts of intensity leakage, which can generate adaptive high-quality DoF rendering effects dynamically, and can be fully implemented in GPU parallelization.

Keywords

Depth of field post-processing GPU adaptive bilateral depth filtering virtual reality 

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References

  1. 1.
    Mather, G.: Image blur as a pictorial depth cue. In: Proceedings of the Royal Society of London. Series B: Biological Sciences, vol. 263(1367), pp. 169–172 (1996)Google Scholar
  2. 2.
    Barsky, B.A., Kosloff, T.J.: Algorithms for rendering depth of field effects in computer graphics, pp. 999–1010 (2008)Google Scholar
  3. 3.
    Cook, R.L., Porter, T., Carpenter, L.: Distributed ray tracing, vol. 18, pp. 137–145 (1984)Google Scholar
  4. 4.
    Haeberli, P., Akeley, K.: The accumulation buffer: Hardware support for high-quality rendering, vol. 24, pp. 309–318 (1990)Google Scholar
  5. 5.
    Potmesil, M., Chakravarty, I.: A lens and aperture camera model for synthetic image generation. ACM SIGGRAPH Computer Graphics 15(3), 297–305 (1981)CrossRefGoogle Scholar
  6. 6.
    Scheuermann, T.: Advanced depth of field. In: GDC 2004, vol. 8 (2004)Google Scholar
  7. 7.
    Hillaire, S., Lecuyer, A., Cozot, R., Casiez, G.: Depth-of-field blur effects for first-person navigation in virtual environments. IEEE Computer Graphics and Applications 28(6), 47–55 (2008)CrossRefGoogle Scholar
  8. 8.
    Rokita, P.: Generating depth of-field effects in virtual reality applications. IEEE Computer Graphics and Applications 16(2), 18–21 (1996)CrossRefGoogle Scholar
  9. 9.
    Zhou, T., Chen, J.X., Pullen, M.: Accurate depth of field simulation in real time, vol. 26, pp. 15–23 (2007)Google Scholar
  10. 10.
    Yu, X., Wang, R., Yu, J.: Real-time depth of field rendering via dynamic light field generation and filtering, vol. 29, pp. 2099–2107 (2010)Google Scholar
  11. 11.
    Kass, M., Lefohn, A., Owens, J.: Interactive depth of field using simulated diffusion on a gpu. Pixar Animation Studios Tech Report (2006)Google Scholar
  12. 12.
    Kraus, M., Strengert, M.: Depth-of-field rendering by pyramidal image processing, vol. 26, pp. 645–654 (2007)Google Scholar
  13. 13.
    Kosloff, T.J., Barsky, B.A.: An algorithm for rendering generalized depth of field effects based on simulated heat diffusion, pp. 1124–1140 (2007)Google Scholar
  14. 14.
    Lee, S., Eisemann, E., Seidel, H.-P.: Real-time lens blur effects and focus control. ACM Transactions on Graphics (TOG) 29(4), 65 (2010)Google Scholar
  15. 15.
    Lee, S., Eisemann, E., Seidel, H.P.: Depth-of-field rendering with multiview synthesis, vol. 28, p. 134 (2009)Google Scholar
  16. 16.
    Tomasi, C., Manduchi, R.: Bilateral filtering for gray and color images, pp. 839–846 (1998)Google Scholar
  17. 17.
    Zhang, B., Allebach, J.P.: Adaptive bilateral filter for sharpness enhancement and noise removal. IEEE Transactions on Image Processing 17(5), 664–678 (2008)MathSciNetCrossRefGoogle Scholar
  18. 18.
    De Silva, D.V.S., Fernando, W.A.C., Kodikaraarachchi, H., Worrall, S.T., Kondoz, A.M.: Adaptive sharpening of depth maps for 3d-tv. Electronics Letters 46(23), 1546–1548 (2010)CrossRefGoogle Scholar
  19. 19.
    Xu, K., Li, Y., Ju, T., Hu, S.-M., Liu, T.Q., Liu, T.-Q.: Efficient affinity-based edit propagation using kd tree, vol. 28, p. 118 (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Shang Wu
    • 1
  • Kai Yu
    • 1
  • Bin Sheng
    • 1
    • 2
  • Feiyue Huang
    • 3
  • Feng Gao
    • 3
  • Lizhuang Ma
    • 1
  1. 1.Department of Computer Science and EngineeringShanghai Jiao Tong UniversityChina
  2. 2.State Key Laboratory of Computer Science, Institute of SoftwareChinese Academy of SciencesChina
  3. 3.Tencent ResearchShanghaiChina

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