Huang Y, Taubmann O, Huang X, Haase V, Lauritsch G, Maier A (2016)
Publication Language: English
Publication Type: Conference contribution, Original article
Publication year: 2016
Publisher: IEEE
Pages Range: 149-152
Conference Proceedings Title: CT-Meeting 2016 Proceedings (The 4th International Meeting on Image Formation in X-Ray Computed Tomography)
Event location: Bamberg, Germany
URI: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2016/Huang16-ANS.pdf
This paper proposes a scale space total variation
(ssTV) algorithm to reduce large scale streaks in limited angle
tomography. The weighted total variation (wTV) algorithm is
able to remove most small scale streaks. However, it fails to
reduce larger streaks since total variation (TV) regularization
is scale-dependent and may regard them as homogeneous areas.
Derived from the wTV algorithm, the proposed ssTV algorithm
applies wTV regularization on the image at different scales using
down-sampling and up-sampling operations and thus can reduce
streaks more effectively. Advantages of the ssTV algorithm are
demonstrated on both 2-D numerical data and a 3-D clinical
dataset.
APA:
Huang, Y., Taubmann, O., Huang, X., Haase, V., Lauritsch, G., & Maier, A. (2016). A New Scale Space Total Variation Algorithm for Limited Angle Tomography. In Marc Kachelrieß (Eds.), CT-Meeting 2016 Proceedings (The 4th International Meeting on Image Formation in X-Ray Computed Tomography) (pp. 149-152). Bamberg, Germany: IEEE.
MLA:
Huang, Yixing, et al. "A New Scale Space Total Variation Algorithm for Limited Angle Tomography." Proceedings of the CT-Meeting 2016, Bamberg, Germany Ed. Marc Kachelrieß, IEEE, 2016. 149-152.
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