skip to main content
research-article

Adaptive image synthesis for compressive displays

Published:21 July 2013Publication History
Skip Abstract Section

Abstract

Recent years have seen proposals for exciting new computational display technologies that are compressive in the sense that they generate high resolution images or light fields with relatively few display parameters. Image synthesis for these types of displays involves two major tasks: sampling and rendering high-dimensional target imagery, such as light fields or time-varying light fields, as well as optimizing the display parameters to provide a good approximation of the target content.

In this paper, we introduce an adaptive optimization framework for compressive displays that generates high quality images and light fields using only a fraction of the total plenoptic samples. We demonstrate the framework for a large set of display technologies, including several types of auto-stereoscopic displays, high dynamic range displays, and high-resolution displays. We achieve significant performance gains, and in some cases are able to process data that would be infeasible with existing methods.

Skip Supplemental Material Section

Supplemental Material

tp046.mp4

References

  1. Adelson, E. H., and Bergen, J. R. 1991. The plenoptic function and the elements of early vision. In Comp. Models of Visual Processing, 3--20.Google ScholarGoogle Scholar
  2. Bertsekas, D. 1997. A New Class of Incremental Gradient Methods for Least Squares Problems. SIAM Journal on Optimization 7, 4, 913--926. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Cook, R., Porter, T., and Carpenter, L. 1984. Distributed ray tracing. In Proc. SIGGRAPH, 137--145. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Cossairt, O. S., Napoli, J., Hill, S. L., Dorval, R. K., and Favalora, G. E. 2007. Occlusion-Capable Multiview Volumetric Three-Dimensional Display. Applied Optics 46, 8, 1244--1250.Google ScholarGoogle ScholarCross RefCross Ref
  5. Didyk, P., Eisemann, E., Ritschel, T., Myszkowski, K., and Seidel, H.-P. 2010. Apparent Display Resolution Enhancement for Moving Images. ACM Trans. Graph. (SIGGRAPH) 29, 4, 113:1--113:8. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Didyk, P., Ritschel, T., Eisemann, E., Myszkowski, K., and Seidel, H.-P. 2011. A Perceptual Model for Disparity. ACM Trans. Graph. (SIGGRAPH) 30, 4, 96:1--96:10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Egan, K., Tseng, Y.-T., Holzschuch, N., Durand, F., and Ramamoorthi, R. 2009. Frequency Analysis and Sheared Reconstruction for Rendering Motion Blur. ACM Trans. Graph. (SIGGRAPH) 28, 3, 93:1--93:13. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Egan, K., Hecht, F., Durand, F., and Ramamoorthi, R. 2011. Frequency Analysis and Sheared Filtering for Shadow Light Fields of Complex Occluders. ACM Trans. Graph. 30, 2, 9:1--9:13. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Friedlander, M., and Schmidt, M. 2012. Hybrid deterministic-stochastic methods for data fitting. SIAM Journal on Scientific Computing 34, 3, 1380--1405.Google ScholarGoogle ScholarCross RefCross Ref
  10. Glassner, A. S., Fishkin, K. P., Marimont, D. H., and Stone, M. C. 1995. Device-Directed Rendering. ACM Trans. Graph. 14, 1, 58--76. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Gotoda, H. 2011. Reduction of Image Blurring in an Autostereoscopic Multilayer Liquid Crystal Display. In Proc. SPIE Stereoscopic Displays and Applications XXII, vol. 7863, 21:1--21:7.Google ScholarGoogle ScholarCross RefCross Ref
  12. Gregson, J., Krimerman, M., Hullin, M. B., and Heidrich, W. 2012. Stochastic Tomography and its Applications in 3D Imaging of Mixing Fluids. ACM Trans. Graph. (SIGGRAPH) 31, 4, 52:1--52:10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Grosse, M., Wetzstein, G., Grundhöfer, A., and Bimber, O. 2010. Coded Aperture Projection. ACM Trans. Graph. 29, 3, 22:1--22:12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Hastings, W. 1970. Monte carlo sampling methods using markov chains and their applications. Biometrika 57, 1, 97--109.Google ScholarGoogle ScholarCross RefCross Ref
  15. Ives, F. E., 1903. Parallax Stereogram and Process of Making Same. U.S. Patent 725,567.Google ScholarGoogle Scholar
  16. Jones, A., McDowall, I., Yamada, H., Bolas, M., and Debevec, P. 2007. Rendering for an interactive 360° light field display. ACM Trans. Graph. (SIGGRAPH) 26, 40:1--40:10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Lanman, D., Hirsch, M., Kim, Y., and Raskar, R. 2010. Content-Adaptive Parallax Barriers: Optimizing Dual-Layer 3D Displays using Low-Rank Light Field Factorization. ACM Trans. Graph. (SIGGRAPH Asia) 29, 163:1--163:10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Lanman, D., Wetzstein, G., Hirsch, M., Heidrich, W., and Raskar, R. 2011. Polarization Fields: Dynamic Light Field Display using Multi-Layer LCDs. ACM Trans. Graph. (SIGGRAPH Asia) 30, 186:1--186:9. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Lehtinen, J., Aila, T., Chen, J., Laine, S., and Durand, F. 2011. Temporal Light Field Reconstruction for Rendering Distribution Effects. ACM Trans. Graph. (SIGGRAPH) 30, 4, 55:1--55:12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Lehtinen, J., Aila, T., Laine, S., and Durand, F. 2012. Reconstructing the Indirect Light Field for Global Illumination. ACM Trans. Graph. (SIGGRAPH) 31, 4, 51:1--51:10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Li, T.-M., Wu, Y.-T., and Chuang, Y.-Y. 2012. SURE-based Optimization for Adaptive Sampling and Reconstruction. ACM Trans. Graph. (SIGGRAPH Asia) 31, 6, 194:1--194:9. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Lippmann, G. 1908. Épreuves réversibles donnant la sensation du relief. Journal of Physics 7, 4, 821--825.Google ScholarGoogle Scholar
  23. Mantiuk, R., Kim, K. J., Rempel, A. G., and Heidrich, W. 2011. HDR-VDP-2: A Calibrated Visual Metric for Visibility and Quality Predictions in all Luminance Conditions. ACM Trans. Graph. (SIGGRAPH) 30, 4, 40:1--40:14. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Marwah, K., Wetzstein, G., Bando, Y., and Raskar, R. 2013. Compressive Ligth Field Photography using Over-complete Dictionaries and Optimized Projections. ACM Trans. Graph. (SIGGRAPH) 32, 4, 1--11. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Metropolis, N., Rosenbluth, A., Rosenbluth, M., Teller, A., and Teller, E. 1953. Equation of state calculations by fast computing machines. The journal of chemical physics 21, 1087--1092.Google ScholarGoogle Scholar
  26. Pharr, M., and Humphreys, G. 2010. Physically based rendering: From theory to implementation. Morgan Kaufmann. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Sajadi, B., Gopi, M., and Majumder, A. 2012. Edge-guided Resolution Enhancement in Projectors via Optical Pixel Sharing. ACM Trans. Graph. (SIGGRAPH) 31, 4, 79:1--79:122. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Seetzen, H., Heidrich, W., Stuerzlinger, W., Ward, G., Whitehead, L., Trentacoste, M., Ghosh, A., and Vorozcovs, A. 2004. High Dynamic Range Display Systems. ACM Trans. Graph. (SIGGRAPH) 23, 3, 760--768. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Sen, P., and Darabi, S. 2011. Compressive Rendering: A Rendering Application of Compressed Sensing. IEEE TVCG 17, 4, 487--499. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Sen, P., Darabi, S., and Xiao, L. 2011. Compressive Rendering of Multidimensional Scenes. In LNCS "Video Processing and Computational Video", 152--183. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Soler, C., Subr, K., Durand, F., Holzschuch, N., and Sillion, F. 2009. Fourier Depth of Field. ACM Trans. Graph. 28, 2, 18:1--18:12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Trentacoste, M., Heidrich, W., Whitehead, L., Seetzen, H., and Ward, G. 2007. Photometric Image Processing for High Dynamic Range Displays. JVCIR 18, 5, 439--451. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Veach, E., and Guibas, L. J. 1997. Metropolis Light Transport. In Proc. SIGGRAPH, 65--76. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Wetzstein, G., Lanman, D., Heidrich, W., and Raskar, R. 2011. Layered 3D: Tomographic Image Synthesis for Attenuation-based Light Field and High Dynamic Range Displays. ACM Trans. Graph. (SIGGRAPH) 30, 95:1--95:11. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. Wetzstein, G., Lanman, D., Hirsch, M., and Raskar, R. 2012. Tensor Displays: Compressive Light Field Synthesis using Multilayer Displays with Directional Backlighting. ACM Trans. Graph. (SIGGRAPH) 31, 80:1--80:11. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Widrow, B., and Stearns, S. 1985. Adaptive signal processing, vol. 1. Prentice-Hall. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Adaptive image synthesis for compressive displays

      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 32, Issue 4
        July 2013
        1215 pages
        ISSN:0730-0301
        EISSN:1557-7368
        DOI:10.1145/2461912
        Issue’s Table of Contents

        Copyright © 2013 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 the author(s) 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: 21 July 2013
        Published in tog Volume 32, Issue 4

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader