http://iet.metastore.ingenta.com
1887

Single image-based HDR image generation with camera response function estimation

Single image-based HDR image generation with camera response function estimation

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Image Processing — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

The high performance of high dynamic range (HDR) image and the limitations of sensors impel to acquire HDR images from low dynamic range (LDR) ones. The most popular methods use multiple LDR images with different exposures of the same scene as input. However, it is difficult to have multiple exposures for most of LDR images. The authors propose a single image-based method to generate HDR image based on camera response function (CRF) reconstruction. The method first estimates the CRF according to the empirical model and the input LDR image. Then, the empirical model of the inverse CRF is constructed according to the relationship between the derivatives of CRF and its inverse function; the optimal solution of inverse CRF is obtained depending on the imaging properties of the edge pixels. Finally, the HDR image is generated by performing the inverse CRF on the original LDR image. The imitation of imaging procedure inherently makes the final HDR image high quality. The experimental results indicate that the proposed approach expand image from the dark and bright regions simultaneously. The resulting metric images also illustrate that their proposed method causes lower total contrast error compared with other single image-based methods.

References

    1. 1)
      • S-C. Hsia , T-T. Kuo .
        1. Hsia, S-C., Kuo, T-T.: ‘High-performance high dynamic range image generation by inverted local patterns’, IET Image Process., 2015, 9, (12), pp. 10831091.
        . IET Image Process. , 12 , 1083 - 1091
    2. 2)
      • T-H. Oh , J-Y. Lee .
        2. Oh, T-H., Lee, J-Y.: ‘Robust high dynamic range imaging by rank minimization’, IEEE Trans. PAMI, 2015, 37, (6), pp. 12191232.
        . IEEE Trans. PAMI , 6 , 1219 - 1232
    3. 3)
      • J.J. McCann , A. Rizzi . (2012)
        3. McCann, J.J., Rizzi, A.: ‘The art and science of HDR imaging’ (John Wiley & Sons, 2012, 1st edn.).
        .
    4. 4)
      • M.D. Fairchild .
        4. Fairchild, M.D.: ‘The HDR photographic survey’. 15th IS&T/SID Color Imaging Conf., Albuquerque, NM, USA, November 5–9, 2007, pp. 233238.
        . 15th IS&T/SID Color Imaging Conf. , 233 - 238
    5. 5)
      • S. Mann , R.W. Picard , R.P. Being .
        5. Mann, S., Picard, R.W., Being, R.P.: ‘Undigital’ with digital cameras: extending dynamic range by combining differently exposed pictures’. Proc. IST 48th Annual Conf., 1995, pp. 442448.
        . Proc. IST 48th Annual Conf. , 442 - 448
    6. 6)
      • P.E. Debevec , J. Malik .
        6. Debevec, P.E., Malik, J.: ‘Recovering high dynamic range radiance maps from photographs’. Proc. SIGGRAPH, Los Angeles, CA, USA, August 1997, pp. 369378.
        . Proc. SIGGRAPH , 369 - 378
    7. 7)
      • S. Nayar , T. Mitsunaga .
        7. Nayar, S., Mitsunaga, T.: ‘High dynamic range imaging: spatially varying pixel exposures’. Proc. IEEE Computer Society Conf. Computer Vision and Pattern Recognition, June 2000, vol. 1, pp. 472479.
        . Proc. IEEE Computer Society Conf. Computer Vision and Pattern Recognition , 472 - 479
    8. 8)
      • H. Zimmer , A. Bruhn , J. Weickert .
        8. Zimmer, H., Bruhn, A., Weickert, J.: ‘Freehand HDR imaging of moving scenes with simultaneous resolution enhancement’, Comput. Graph. Forum, 2011, 30, (2), pp. 405414.
        . Comput. Graph. Forum , 2 , 405 - 414
    9. 9)
      • K. Saito .
        9. Saito, K.: ‘Electronic image pickup device’. Japanese Patent 08–340486, 1996.
        .
    10. 10)
      • E. Ikeda .
        10. Ikeda, E.: ‘Image data processing apparatus for processing combined image signals in order to extend dynamic range’. U.S. Patent 5801773, 1998.
        .
    11. 11)
      • R.A. Street .
        11. Street, R.A.: ‘High dynamic range segmented pixel sensor array’. U.S. Patent 5789737, 1998.
        .
    12. 12)
      • M. Schober , J. Keinert , M. Ziegler .
        12. Schober, M., Keinert, J., Ziegler, M., et al: ‘Valuation of a high dynamic range video camera with non-regular sensor’. Proc. SPIE Electron. Imaging, 2013, pp. 86600M1–86600M–12.
        . Proc. SPIE Electron. Imaging , 86600M - 1–86600M–12
    13. 13)
      • F. Banterle , M. Dellepiane , R. Scopigno .
        13. Banterle, F., Dellepiane, M., Scopigno, R.: ‘Enhancement of low dynamic range videos using high dynamic range backgrounds’. Proc. EUROGRAPHICS, April 2011, pp. 5762.
        . Proc. EUROGRAPHICS , 57 - 62
    14. 14)
      • A. Chalmers , G. Bonnet , F. Banterle .
        14. Chalmers, A., Bonnet, G., Banterle, F., et al: ‘A high-dynamic-range video solution’. Proc. 2nd ACM SIGGRAPH Conf. Exhibition Asia, 2009, pp. 7172.
        . Proc. 2nd ACM SIGGRAPH Conf. Exhibition Asia , 71 - 72
    15. 15)
      • Y. Huo , F. Yang , V. Brost .
        15. Huo, Y., Yang, F., Brost, V.: ‘Dodging and burning inspired inverse tone mapping algorithm’, J. Comput. Inf. Syst., 2013, 9, (9), pp. 34613468.
        . J. Comput. Inf. Syst. , 9 , 3461 - 3468
    16. 16)
      • B. Masia , S. Agustin , S. Fleming .
        16. Masia, B., Agustin, S., Fleming, S., et al: ‘Evaluation of reverse tone mapping through varying exposure conditions’, ACM Trans. Graph., 2009, 28, (5), pp. 18.
        . ACM Trans. Graph. , 5 , 1 - 8
    17. 17)
      • F. Banterle , K. Debattista , A. Artusi .
        17. Banterle, F., Debattista, K., Artusi, A., et al: ‘High dynamic range imaging and low dynamic range expansion for generating HDR content’, Comput. Graph. Forum, 2009, 28, (8), pp. 23432367.
        . Comput. Graph. Forum , 8 , 2343 - 2367
    18. 18)
      • H. Landis .
        18. Landis, H.: ‘Production-ready global illumination’. SIGGRAPH 2002 Course Notes #16, RenderMan in Production, 2002, pp. 87101.
        . , 87 - 101
    19. 19)
      • A.O. Akyuz , R. Fleming , O. Sorkine .
        19. Akyuz, A.O., Fleming, R., Sorkine, O., et al: ‘Do HDR displays support LDR content?: a psychophysical evaluation’, ACM Trans. Graph., 2007, 26, (3), pp. 17.
        . ACM Trans. Graph. , 3 , 1 - 7
    20. 20)
      • L. Meylan , S. Daly , S. Susstrunk .
        20. Meylan, L., Daly, S., Susstrunk, S.: ‘The reproduction of specular highlights on high dynamic range displays’. Proc. IST/SID 14th Colour Imaging Conf., Scottsdale, USA, November 2006, pp. 333338.
        . Proc. IST/SID 14th Colour Imaging Conf. , 333 - 338
    21. 21)
      • L. Meylan , S. Daly , S. Susstrunk .
        21. Meylan, L., Daly, S., Susstrunk, S.: ‘Tone mapping for high dynamic range displays’. Proc. IS&T/SPIE Electronic Imaging: Human Vision and Electronic Imaging XII, San Jose, CA, USA, January 2007, pp. 649210-1649210-12.
        . Proc. IS&T/SPIE Electronic Imaging: Human Vision and Electronic Imaging XII , 649210 - 649211
    22. 22)
      • P. Didyk , R. Mantiuk , M. Hein .
        22. Didyk, P., Mantiuk, R., Hein, M., et al: ‘Enhancement of bright video features for HDR displays’, Comput. Graph. Forum, 2008, 27, (4), pp. 12651274.
        . Comput. Graph. Forum , 4 , 1265 - 1274
    23. 23)
      • F. Banterle , P. Ledda , K. Debattista .
        23. Banterle, F., Ledda, P., Debattista, K., et al: ‘Inverse tone mapping’. Proc. 4th Int. Conf. Computer Graphics and Interactive Techniques in Australasia and Southeast Asia, NY, USA, 2006, pp. 349356.
        . Proc. 4th Int. Conf. Computer Graphics and Interactive Techniques in Australasia and Southeast Asia , 349 - 356
    24. 24)
      • F. Banterle , P. Ledda , K. Debattista .
        24. Banterle, F., Ledda, P., Debattista, K., et al: ‘A framework for inverse tone mapping’, Visual Comput., 2007, 23, (7), pp. 467478.
        . Visual Comput. , 7 , 467 - 478
    25. 25)
      • A.G. Rempel , M. Trentacoste , H. Seetzen .
        25. Rempel, A.G., Trentacoste, M., Seetzen, H., et al: ‘Ldr2hdr: on-the-fly reverse tone mapping of legacy video and photographs’, ACM Trans. Graph., 2007, 26, (3), article 39 pp. 16.
        . ACM Trans. Graph. , 3 , 1 - 6
    26. 26)
      • R.P. Kovaleski , M.M. Oliveira .
        26. Kovaleski, R.P., Oliveira, M.M.: ‘High quality brightness enhancement functions for real-time reverse tone mapping’, Visual Comput., 2009, 25, (5–7), pp. 539547.
        . Visual Comput. , 539 - 547
    27. 27)
      • Y.Q. Huo , F. Yang , V. Brost .
        27. Huo, Y.Q., Yang, F., Brost, V., et al: ‘LDR image to HDR image mapping with overexposure preprocessing’, IEICE Trans. Fundam., 2013, E96-A, (6), pp. 11851194.
        . IEICE Trans. Fundam. , 6 , 1185 - 1194
    28. 28)
      • Y.Q. Huo , F. Yang , V. Brost .
        28. Huo, Y.Q., Yang, F., Brost, V.: ‘High dynamic range image generation from single low dynamic range image’, IET Image Process., 2016, 10, (3), pp. 198205.
        . IET Image Process. , 3 , 198 - 205
    29. 29)
      • L. Wang , L. Wei , K. Zhou .
        29. Wang, L., Wei, L., Zhou, K., et al: ‘High dynamic range image hallucination’. Eurographics Symp. Rendering, 2007.
        . Eurographics Symp. Rendering
    30. 30)
      • T. Wang , C. Chiu , W. Wu .
        30. Wang, T., Chiu, C., Wu, W., et al: ‘Pseudo-multiple-exposure-based tone fusion with local region adjustment’, IEEE Trans. Multimedia, 2015, 17, (4), pp. 470484.
        . IEEE Trans. Multimedia , 4 , 470 - 484
    31. 31)
      • T. Wang , C. Chiu .
        31. Wang, T., Chiu, C.: ‘Low visual difference virtual high dynamic range image synthesizer from a single legacy image’. 18th IEEE Int. Conf. Image Processing, Brussels, Belgium, September 2011, pp. 22652268.
        . 18th IEEE Int. Conf. Image Processing , 2265 - 2268
    32. 32)
      • Y.Q. Huo , F. Yang , L. Dong .
        32. Huo, Y.Q., Yang, F., Dong, L., et al: ‘Physiological inverse tone mapping based on retina response’, Visual Comput., 2014, 30, (5), pp. 507517.
        . Visual Comput. , 5 , 507 - 517
    33. 33)
      • M.D. Grossberg , S.K. Nayar .
        33. Grossberg, M.D., Nayar, S.K.: ‘Modeling the space of camera response functions’, IEEE Trans. PAMI, 2004, 26, (10), pp. 12721282.
        . IEEE Trans. PAMI , 10 , 1272 - 1282
    34. 34)
      • S. Lin , J. Gu , S. Yamazaki .
        34. Lin, S., Gu, J., Yamazaki, S., et al: ‘Radiometric calibration from a single image’. Proc. 2004 IEEE Computer Society Conf. Computer Vision and Pattern Recognition, Washington, DC, USA, July 2004, pp. II-938II-945.
        . Proc. 2004 IEEE Computer Society Conf. Computer Vision and Pattern Recognition , II - 938
    35. 35)
      • T.O. Aydin , R. Mantiuk , K. Myszkowski .
        35. Aydin, T.O., Mantiuk, R., Myszkowski, K., et al: ‘Dynamic range independent image quality assessment’, ACM Trans. Graph, 2008, 27, (3), article 69 pp. 110.
        . ACM Trans. Graph , 3 , 1 - 10
    36. 36)
      • E. Reinhard , M. Stark , P. Shirley .
        36. Reinhard, E., Stark, M., Shirley, P., et al: ‘Photographic tone reproduction for digital images’, ACM Trans. Graph., 2002, 21, (3), pp. 267276.
        . ACM Trans. Graph. , 3 , 267 - 276
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-ipr.2016.1075
Loading

Related content

content/journals/10.1049/iet-ipr.2016.1075
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address