@article{Farago:tv5034,
    author = "Farag{\'{o}}, Tom{\'{a}}{\v{s}} and Gasilov, Sergey and Emslie, Iain and Zuber, Marcus and Helfen, Lukas and Vogelgesang, Matthias and Baumbach, Tilo",
    title = "{{\it Tofu}: a fast, versatile and user-friendly image processing toolkit for computed tomography}",
    journal = "Journal of Synchrotron Radiation",
    year = "2022",
    volume = "29",
    number = "3",
    pages = "916--927",
    month = "May",
    doi = {10.1107/S160057752200282X},
    url = {https://doi.org/10.1107/S160057752200282X},
    abstract = {{\it Tofu} is a toolkit for processing large amounts of images and for tomographic reconstruction. Complex image processing tasks are organized as workflows of individual processing steps. The toolkit is able to reconstruct parallel and cone beam as well as tomographic and laminographic geometries. Many pre- and post-processing algorithms needed for high-quality 3D reconstruction are available, {\it e.g.} phase retrieval, ring removal and de-noising. {\it Tofu} is optimized for stand-alone GPU workstations on which it achieves reconstruction speed comparable with costly CPU clusters. It automatically utilizes all GPUs in the system and generates 3D reconstruction code with minimal number of instructions given the input geometry (parallel/cone beam, tomography/laminography), hence yielding optimal run-time performance. In order to improve accessibility for researchers with no previous knowledge of programming, {\it tofu} contains graphical user interfaces for both optimization of 3D reconstruction parameters and batch processing of data with pre-configured workflows for typical computed tomography reconstruction. The toolkit is open source and extensive documentation is available for both end-users and developers. Thanks to the mentioned features, {\it tofu} is suitable for both expert users with specialized image processing needs ({\it e.g.} when dealing with data from custom-built computed tomography scanners) and for application-specific end-users who just need to reconstruct their data on off-the-shelf hardware.},
keywords = {tomography, laminography, parallel beam, cone beam, 3D reconstruction, phase retrieval, artifact removal, GPU computing, user interface, batch processing, visual programming},
}

@article{MOREL2012342,
    title = {Fourier implementation of Poisson image editing},
    journal = {Pattern Recognition Letters},
    volume = {33},
    number = {3},
    pages = {342-348},
    year = {2012},
    issn = {0167-8655},
    doi = {https://doi.org/10.1016/j.patrec.2011.10.010},
    url = {https://www.sciencedirect.com/science/article/pii/S0167865511003564},
    author = {J.-M. Morel and A.B. Petro and C. Sbert},
    keywords = {Image editing, Fourier transform, Poisson equation, Local contrast enhancement},
    abstract = {Poisson editing, introduced in 2003, is becoming a technique with major applications in many different domains of image processing and computer graphics. This letter presents an exact and fast Fourier implementation of the Poisson editing equation proposed in (Pérez et al., 2003). The proposed algorithm can handle well all Poisson editing methods that are currently implemented with finite differences and multigrid methods. But it also authorizes fast complex editing strategies where the edited region is obtained by an algorithm instead of a manual selection. The selected region can therefore have a complex topology without additional computational cost. In this letter the proposed method is applied to a classic local contrast enhancement principle introduced in (Caselles et al., 1999). The manual selection of the dark regions is replaced by a lower threshold and the method becomes fast, efficient, level-line preserving, and interactive. The proposed method can be tried on line on any uploaded image at http://www.ipol.im/pub/demo/lmps_selective_contrast_adjustment/.}
}

@article{moisan2011periodic,
  title={Periodic plus smooth image decomposition},
  author={Moisan, Lionel},
  journal={Journal of Mathematical Imaging and Vision},
  volume={39},
  pages={161--179},
  year={2011},
  publisher={Springer}
}
