Performance engineering to achieve real-time high dynamic range imaging

Journal article

Publication Details

Author(s): Köstler H, Stürmer M, Pohl T
Journal: Journal of Real-Time Image Processing
Publisher: Springer Verlag (Germany)
Publication year: 2013
Pages range: 1-13
ISSN: 1861-8200


Image-processing applications like high dynamic range imaging can be done efficiently in the gradient space. For it, the image has to be transformed to gradient space and back. While the forward transformation to gradient space is fast by using simple finite differences, the backward transformation requires the solution of a partial differential equation. Although one can use an efficient multigrid solver for the backward transformation, it shows that a straightforward implementation of the standard algorithm does not lead to satisfactory runtime results for real-time high dynamic range compression of larger 2D X-ray images even on GPUs. Therefore, we do a rigorous performance analysis and derive a performance model for our multigrid algorithm that guides us to an improved implementation, where we achieve an overall performance of more than 25 frames per second for 16.8 Megapixel images doing full high dynamic range compression including data transfers between CPU and GPU. Together with a simple OpenGL visualization it becomes possible to perform real-time parameter studies on medical data sets. © 2013 Springer-Verlag Berlin Heidelberg.

FAU Authors / FAU Editors

Köstler, Harald Prof. Dr.
Lehrstuhl für Informatik 10 (Systemsimulation)
Stürmer, Markus
Lehrstuhl für Informatik 10 (Systemsimulation)

How to cite

Köstler, H., Stürmer, M., & Pohl, T. (2013). Performance engineering to achieve real-time high dynamic range imaging. Journal of Real-Time Image Processing, 1-13.

Köstler, Harald, Markus Stürmer, and Thomas Pohl. "Performance engineering to achieve real-time high dynamic range imaging." Journal of Real-Time Image Processing (2013): 1-13.


Last updated on 2018-25-09 at 15:23