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International Conference on Image Analysis and Processing

ICIAP 2022: Image Analysis and Processing – ICIAP 2022 pp 467–478Cite as

One-Shot HDR Imaging via Stereo PFA Cameras

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13232))

Abstract

High Dynamic Range (HDR) imaging techniques aim to increase the range of luminance values captured from a scene. The literature counts many approaches to get HDR images out of low-range camera sensors, however most of them rely on multiple acquisitions producing ghosting effects when moving objects are present.

In this paper we propose a novel HDR reconstruction method exploiting stereo Polarimetric Filter Array (PFA) cameras to simultaneously capture the scene with different polarized filters, producing intensity attenuations that can be related to the light polarization state. An additional linear polarizer is mounted in front of one of the two cameras, raising the degree of polarization of rays captured by the sensor. This leads to a larger attenuation range between channels regardless the scene lighting condition. By merging the data acquired by the two cameras, we can compute the actual light attenuation observed by a pixel at each channel and derive an equivalent exposure time, producing a HDR picture from a single polarimetric shot. The proposed technique results comparable to classic HDR approaches using multiple exposures, with the advantage of being a one-shot method.

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Notes

  1. 1.

    Considering that we are acquiring a scene with a high dynamic range, it will be unavoidable to over- or under-expose some areas.

  2. 2.

    We empirically observed that \(\sigma =0.2\) usually gives satisfactory results.

References

  1. Sharif, A.S., Naqvi, R.A., Biswas, M., Kim, S.: A two-stage deep network for high dynamic range image reconstruction. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 550–559 (2021)

    Google Scholar 

  2. Banterle, F., et al.: High dynamic range imaging and low dynamic range expansion for generating HDR content. In: Computer Graphics Forum, vol. 28, pp. 2343–2367. Wiley Online Library (2009)

    Google Scholar 

  3. Banterle, F., Ledda, P., Debattista, K., Chalmers, A.: Inverse tone mapping. In: Proceedings of the 4th International Conference on Computer Graphics and Interactive Techniques in Australasia and Southeast Asia, pp. 349–356 (2006)

    Google Scholar 

  4. Cronin, T.W., Marshall, J.: Patterns and properties of polarized light in air and water. Philos. Trans. Royal Soc. B Biol. Sci. 366(1565), 619–626 (2011)

    Article  Google Scholar 

  5. Debevec, P.E., Malik, J.: Recovering high dynamic range radiance maps from photographs. In: ACM SIGGRAPH 2008 Classes, pp. 1–10 (2008)

    Google Scholar 

  6. Eilertsen, G., Kronander, J., Denes, G., Mantiuk, R.K., Unger, J.: HDR image reconstruction from a single exposure using deep CNNs. ACM Trans. Graph. (TOG) 36(6), 1–15 (2017)

    Article  Google Scholar 

  7. Endo, Y., Kanamori, Y., Mitani, J.: Deep reverse tone mapping. ACM Trans. Graph. 36(6), 1–10 (2017). (Proc. of SIGGRAPH ASIA 2017)

    Google Scholar 

  8. Farnebäck, G.: Two-frame motion estimation based on polynomial expansion. In: Bigun, J., Gustavsson, T. (eds.) SCIA 2003. LNCS, vol. 2749, pp. 363–370. Springer, Heidelberg (2003). https://doi.org/10.1007/3-540-45103-X_50

    Chapter  Google Scholar 

  9. Goldstein, D.H.: Polarized Light. CRC Press, Boca Raton (2017)

    Book  Google Scholar 

  10. Kalantari, N.K., Ramamoorthi, R., et al.: Deep high dynamic range imaging of dynamic scenes. ACM Trans. Graph. 36(4), 144–1 (2017)

    Article  Google Scholar 

  11. Khan, E.A., Akyuz, A.O., Reinhard, E.: Ghost removal in high dynamic range images. In: 2006 International Conference on Image Processing, pp. 2005–2008. IEEE (2006)

    Google Scholar 

  12. Khan, Z., Khanna, M., Raman, S.: FHDR: HDR image reconstruction from a single LDR image using feedback network. In: 2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP), pp. 1–5. IEEE (2019)

    Google Scholar 

  13. Kovaleski, R.P., Oliveira, M.M.: High-quality reverse tone mapping for a wide range of exposures. In: 2014 27th SIBGRAPI Conference on Graphics, Patterns and Images, pp. 49–56. IEEE (2014)

    Google Scholar 

  14. Kupinski, M.K., Bradley, C.L., Diner, D.J., Xu, F., Chipman, R.A.: Angle of linear polarization images of outdoor scenes. Opt. Eng. 58(8), 082419 (2019)

    Article  Google Scholar 

  15. Lee, S., An, G.H., Kang, S.-J.: Deep recursive HDRI: inverse tone mapping using generative adversarial networks. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11206, pp. 613–628. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-01216-8_37

    Chapter  Google Scholar 

  16. Liu, Y.L., et al.: Single-image HDR reconstruction by learning to reverse the camera pipeline. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 1651–1660 (2020)

    Google Scholar 

  17. Marnerides, D., Bashford-Rogers, T., Hatchett, J., Debattista, K.: ExpandNet: a deep convolutional neural network for high dynamic range expansion from low dynamic range content. In: Computer Graphics Forum, vol. 37, pp. 37–49. Wiley Online Library (2018)

    Google Scholar 

  18. McCann, J.J., Rizzi, A.: The Art and Science of HDR Imaging, vol. 26. Wiley, New York (2011)

    Book  Google Scholar 

  19. Mertens, T., Kautz, J., Van Reeth, F.: Exposure fusion: a simple and practical alternative to high dynamic range photography. In: Computer Graphics Forum, vol. 28, pp. 161–171. Wiley Online Library (2009)

    Google Scholar 

  20. Mihoubi, S., Lapray, P.J., Bigué, L.: Survey of demosaicking methods for polarization filter array images. Sensors 18(11), 3688 (2018)

    Article  Google Scholar 

  21. Mitsunaga, T., Nayar, S.K.: Radiometric self calibration. In: Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149), vol. 1, pp. 374–380. IEEE (1999)

    Google Scholar 

  22. Pistellato, M., Bergamasco, F., Fatima, T., Torsello, A.: Deep demosaicing for polarimetric filter array cameras. IEEE Trans. Image Process. 31, 2017–2026 (2022). https://doi.org/10.1109/TIP.2022.3150296

    Article  Google Scholar 

  23. Prabhakar, K.R., Babu, R.V.: Ghosting-free multi-exposure image fusion in gradient domain. In: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1766–1770. IEEE (2016)

    Google Scholar 

  24. Reinhard, E., Heidrich, W., Debevec, P., Pattanaik, S., Ward, G., Myszkowski, K.: High Dynamic Range Imaging: Acquisition, Display, and Image-Based Lighting. Morgan Kaufmann, San Francisco (2010)

    Google Scholar 

  25. Santos, M.S., Ren, T.I., Kalantari, N.K.: Single image HDR reconstruction using a CNN with masked features and perceptual loss. arXiv preprint arXiv:2005.07335 (2020)

  26. Santos, M.S., Tsang, R., Khademi Kalantari, N.: Single image HDR reconstruction using a CNN with masked features and perceptual loss. ACM Trans. Graph. 39(4) (2020). https://doi.org/10.1145/3386569.3392403

  27. Umow, N.: Chromatische depolarisation durch lichtzerstreuung. Phys. Z 6, 674–676 (1905)

    Google Scholar 

  28. Wang, Z., Simoncelli, E.P., Bovik, A.C.: Multiscale structural similarity for image quality assessment. In: The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, vol. 2, pp. 1398–1402. IEEE (2003)

    Google Scholar 

  29. Wu, X., Zhang, H., Hu, X., Shakeri, M., Fan, C., Ting, J.: HDR reconstruction based on the polarization camera. IEEE Robot. Autom. Lett. 5(4), 5113–5119 (2020)

    Article  Google Scholar 

  30. Yang, X., Xu, K., Song, Y., Zhang, Q., Wei, X., Lau, R.W.: Image correction via deep reciprocating HDR transformation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1798–1807 (2018)

    Google Scholar 

  31. Yu, Y., Zhu, D., Smith, W.A.: Shape-from-polarisation: a nonlinear least squares approach. In: Proceedings of the IEEE International Conference on Computer Vision Workshops, pp. 2969–2976 (2017)

    Google Scholar 

  32. Zappa, C.J., Banner, M.L., Schultz, H., Corrada-Emmanuel, A., Wolff, L.B., Yalcin, J.: Retrieval of short ocean wave slope using polarimetric imaging. Meas. Sci. Technol. 19(5), 055503 (2008)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. DAIS, Università Ca’Foscari Venezia, 155, via Torino, Venice, Italy

    Tehreem Fatima, Mara Pistellato, Andrea Torsello & Filippo Bergamasco

Authors
  1. Tehreem Fatima
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  2. Mara Pistellato
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  3. Andrea Torsello
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  4. Filippo Bergamasco
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Corresponding author

Correspondence to Mara Pistellato .

Editor information

Editors and Affiliations

  1. Boston University, Boston, MA, USA

    Stan Sclaroff

  2. National Research Council, Lecce, Italy

    Cosimo Distante

  3. National Research Council, Lecce, Italy

    Marco Leo

  4. University of Catania, Catania, Italy

    Giovanni M. Farinella

  5. Technische Universität München, Garching, Germany

    Federico Tombari

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Fatima, T., Pistellato, M., Torsello, A., Bergamasco, F. (2022). One-Shot HDR Imaging via Stereo PFA Cameras. In: Sclaroff, S., Distante, C., Leo, M., Farinella, G.M., Tombari, F. (eds) Image Analysis and Processing – ICIAP 2022. ICIAP 2022. Lecture Notes in Computer Science, vol 13232. Springer, Cham. https://doi.org/10.1007/978-3-031-06430-2_39

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  • DOI: https://doi.org/10.1007/978-3-031-06430-2_39

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  • Print ISBN: 978-3-031-06429-6

  • Online ISBN: 978-3-031-06430-2

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