Abstract
A large class of techniques for image processing is based on manipulation of the gradient field of an image. These techniques have high computational complexity, due to the need to solve an inverse problem, taking the form of a Poisson equation, to find the output image that best matches a manipulated gradient field. This work studies hardware-friendly techniques, appropriate for implementation on a field-programmable gate array implementation and embeddable inside a camera, for approximating this solution. Fattal’s operator for the dynamic range compression of high dynamic range images is studied as a representative example application. A family of methods, inspired by Fattal’s operator but with significantly lower computational complexity, solves the inverse problem in a moving window of small size. In this paper, a study is conducted to understand the role that the boundary conditions and the size of the window play in the quality of the resulting output image and the size of the hardware. The impact of using single-scale and multi-scale approaches to compute the attenuation factors needed for Fattal’s operator is also considered.
Similar content being viewed by others
References
Banterle, F., Artusi, A., Debattista, K., Chalmers, A.: Advanced High Dynamic Range Imaging: Theory and Practice, 1st edn. CRC Press (AK Peters), Natick, MA (2011)
Reinhard, E., Ward, G., Pattanaik, S., Debevec, P.: High Dynamic Range Imaging. Morgan Kaufmann, Boston (2005)
Reinhard, E., Stark, M., Shirley, P., Ferwerda, J.: Photographic tone reproduction for digital images. In: Proceedings of the 29th Annual Conference on Computer Graphics and Interactive Techniques, pp. 267–276, July 2002
Fattal, R., Lischinski, D, Werman, M.: Gradient domain high dynamic range compression. In: Proceedings of the 29th Annual Conference on Computer Graphics and Interactive Techniques, pp. 249–256, 2002
Agrawal, A., Raskar, R.: Gradient domain manipulation techniques in vision and graphics. Course offered at the 11th IEEE International Conference on Computer Vision, 2007, downloaded on January 29, 2013 from ftp://ftp.umiacs.umd.edu/pub/aagrawal/ICCV07Course/AmitSection3.pdf
Kazhdan, M., Hoppe, H.: Streaming multigrid for gradient-domain operations on large images. In: ACM Transactions on Graphics, pp. 1–10, 2008
Agarwala, A.: Efficient gradient-domain compositing using quadtrees. ACM Trans. Graph. 26(3), 1–5 (2007)
Vytla, L., Hassan, F., Carletta, J.E.: A real-time implementation of gradient domain high dynamic range compression using a local Poisson solver. J. Real-Time Image Proc. 6(4), 1–15 (2011)
Hassan, F., Vytla, L., Carletta, J. E.: Exploiting redundancy to solve the Poisson equation using local information. In: IEEE International Conference on Image Processing, 2009
Wang, T.-H., Ke, W.-M., Zwao, D.-C., Chen, F.-C.: Block-based gradient domain high dynamic range compression design for real-time applications. Proc. IEEE Int. Conf. Image Process. 3, 561–564 (2007)
Debevec, P.E., Malik, J.: Recovering high dynamic range radiance maps from photographs. In: Proceedings of the 24th Annual Conference on Computer Graphics and Interactive Techniques, pp. 369–378, 1997
Smith, K., Krawczyk, G., Myszkowski, K., Seidel, H.-P.: Beyond tone mapping: enhanced depiction of tone mapped HDR images. In: Computer graphics forum (Proc. of EUROGRAPHICS) 25, 3, pp. 427–438, 2006
Aydin, T.O., Mantiuk, R., Myszkowski, K., Seidel, H.S.: Dynamic range independent image quality assessment. In: SIGGRAPH. ACM Trans, Graph (2008)
Hassan, F., Carletta, J.E.: An FPGA-based architecture for a tone mapping operator. J. Real-Time Image Proc. 2(4), 293–308 (2007)
Perez, P., Gangnet, M., Blake, A.: Poisson image editing. ACM Trans. Graph. 22(3), 313–318 (2003)
Sun, J., Jia, J., Tang, C.-K., Shum, H.-Y.: Poisson matting. ACM Trans. Graph. 23(3), 315–321 (2004)
Raskar, R., Hie, A., Yu, J.: Image fusion for context enhancement and video surrealism. In: Proceedings of ACM SIGGRAPH Courses, pp. 85–93, 2005
Levin, A., Zomet, A., Peleg, S., Weiss, Y.: Seamless image stitching in the gradient domain. Lecture Notes in European Conference on Computer Vision 3024, 377–389 (2004)
Author information
Authors and Affiliations
Corresponding author
Additional information
J.E. Carletta is Member of IEEE.
Rights and permissions
About this article
Cite this article
Liu, J., Hassan, F. & Carletta, J.E. A study of hardware-friendly methods for gradient domain tone mapping of high dynamic range images. J Real-Time Image Proc 12, 165–181 (2016). https://doi.org/10.1007/s11554-013-0365-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11554-013-0365-y