Abstract
Image reconstruction is an active research field and plays an important role in many applications . In this paper, we propose a new approach. Firstly, we introduce the minimum total variation (TV) criterion in the optimization process of image reconstruction; secondly, we introduce the level set method to obtain the solution. The TV principle has been studied intensively in the community of image processing and computer vision. The TV constrained minimization problem is convex and has a unique solution. The standard level set method provides the way to get the solution. We validated the proposed model on both toy data and real data. The experimental results show that the TV principle has the advantages of reducing noise and artifacts and preserving edges. The experiments also indicate that the proposed method is suitable and applicable to practical applications.
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Yu, G., Li, L., Gu, J., Zhang, L. (2005). Total Variation Based Iterative Image Reconstruction. In: Liu, Y., Jiang, T., Zhang, C. (eds) Computer Vision for Biomedical Image Applications. CVBIA 2005. Lecture Notes in Computer Science, vol 3765. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11569541_53
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DOI: https://doi.org/10.1007/11569541_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29411-5
Online ISBN: 978-3-540-32125-5
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