FAW for Multi-exposure Fusion Features

  • Michael May
  • Martin Turner
  • Tim Morris
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7087)


This paper introduces a process where fusion features assist matching scale invariant feature transform (SIFT) image features from high contrast scenes. FAW defines the order for extracting features: features, alignment then weighting. The process uses three quality measures to select features from a series of differently exposed images and select a subset of the features in favour of those areas that are defined as well exposed from the different images. The results show an advantage in using these features over features extracted from the common alternative techniques of exposure fusion and tone mapping which extract the features as AWF; alignment, weighting then features. This paper also shows that the process allows for a more robust response when using misaligned or stereoscopic image sets.


feature fusion SIFT HDR LDR tone mapping exposure fusion stereo 


  1. 1.
    Debevec, P., Malik, J.: Recovering high dynamic range radiance maps from photographs. In: ACM SIGGRAPH Classes, pp. 1–10. ACM (2008)Google Scholar
  2. 2.
    Devlin, K., Reinhard, E.: Dynamic Range Reduction Inspired by Photoreceptor Physiology. IEEE TVCG 11(1), 13–24 (2005)Google Scholar
  3. 3.
    Drago, F., Myszkowski, K., Annen, T., Chiba, N.: Adaptive logarithmic mapping for displaying high contrast scenes. CGF 22, 419–426 (2003)Google Scholar
  4. 4.
    Durand, F., Dorsey, J.: Fast bilateral filtering for the display of high-dynamic-range images. ACM TOG 21, 257–266 (2002)Google Scholar
  5. 5.
    Fattal, R., Lischinski, D., Werman, M.: Gradient domain high dynamic range compression. ACM TOG 21(3), 249–256 (2002)CrossRefGoogle Scholar
  6. 6.
    Helmer, S., Meger, D., Muja, M., Little, J.J., Lowe, D.G.: Multiple Viewpoint Recognition and Localization. In: Kimmel, R., Klette, R., Sugimoto, A. (eds.) ACCV 2010, Part I. LNCS, vol. 6492, pp. 464–477. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  7. 7.
    Larson, G., Rushmeier, H., Piatko, C.: A visibility matching tone reproduction operator for high dynamic range scenes. IEEE TVCG 3(4), 291–306 (1997)Google Scholar
  8. 8.
    Li, Y., Sharan, L., Adelson, E.: Compressing and companding high dynamic range images with subband architectures. ACM TOG 24, 836–844 (2005)CrossRefGoogle Scholar
  9. 9.
    Lowe, D.: Object recognition from local scale-invariant features. In: ICCV, vol. 2, p. 1150 (1999)Google Scholar
  10. 10.
    Lowe, D.: Distinctive image features from scale-invariant keypoints. IJCV 60(2), 91–110 (2004)CrossRefGoogle Scholar
  11. 11.
    Mann, S., Picard, R., Section, Massachusetts Institute Technology Perceptual Computing: On being ’undigital’ with digital cameras: Extending dynamic range by combining differently exposed pictures (1995)Google Scholar
  12. 12.
    May, M., Morris, T., Markham, K., Crowther, W.J., Turner, M.J.: Towards Object Recognition using HDR Video, Stereoscopic Depth Information and SIFT. In: EG UK TPCG (2009)Google Scholar
  13. 13.
    May, M., Turner, M.J., Morris, T.: Analysing False Positives and 3D Structure to Create Intelligent Thresholding and Weighting Functions for SIFT Features. In: Ho, Y.-S. (ed.) PSIVT 2011, Part I. LNCS, vol. 7087, pp. 191–202. Springer, Heidelberg (2011)Google Scholar
  14. 14.
    Mertens, T., Kautz, J., Van Reeth, F.: Exposure fusion: A simple and practical alternative to high dynamic range photography. CGF 28, 161–171 (2009)Google Scholar
  15. 15.
    Mertens, T., Kautz, J., Van Reeth, F.: Exposure fusion. In: PG. pp. 382–390. IEEE (October 2007)Google Scholar
  16. 16.
    Reinhard, E.: Dynamic range reduction inspired by photoreceptor physiology. IEEE TVCG 11(1), 13–24 (2005)Google Scholar
  17. 17.
    Reinhard, E.: High dynamic range imaging: acquisition, display, and image-based lighting. Morgan Kaufmann (2006)Google Scholar
  18. 18.
    Reinhard, E., Stark, M., Shirley, P., Ferwerda, J.: Photographic tone reproduction for digital images. ACM TOG 21(3), 267–276 (2002)CrossRefGoogle Scholar
  19. 19.
    Tico, M., Gelfand, N., Pulli, K.: Motion-blur-free exposure fusion. In: IEEE ICIP, pp. 3321–3324, No. I (2010)Google Scholar
  20. 20.
    Tomaszewska, A., Mantiuk, R.: Image registration for multi-exposure high dynamic range image acquisition. In: WSCG, pp. 49–56 (2007)Google Scholar
  21. 21.
    Tumblin, J., Rushmeier, H.: Tone reproduction for realistic images. IEEE CGA 13(6), 42–48 (1993)Google Scholar
  22. 22.
    Xiao, F., DiCarlo, J., Catrysse, P., Wandell, B.: High dynamic range imaging of natural scenes. In: CIC, pp. 337–442 (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Michael May
    • 1
  • Martin Turner
    • 1
  • Tim Morris
    • 1
  1. 1.The University of ManchesterUK

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