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- W2529409853 abstract "An edge-preserving iterative reconstruction method using convex median priors is presented for transmission tomography. The convex median prior [1] is modeled as a weighted sum of the absolute distance between two parameters, one for the underlying image field and the other for an auxiliary field in register with the underlying image field. To optimize a convex objective function of the two parameters, an alternating joint minimization algorithm based on a separable paraboloidal surrogates algorithm is derived. Our experimental results indicate that, while the standard median prior often removes fine details when they occupy less than half of the window elements, the weighted median prior can preserve those by properly adjusting the center weight." @default.
- W2529409853 created "2016-10-14" @default.
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- W2529409853 date "2015-10-01" @default.
- W2529409853 modified "2023-09-26" @default.
- W2529409853 title "Edge-preserving iterative reconstruction for transmission tomography using convex weighted median priors" @default.
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- W2529409853 doi "https://doi.org/10.1109/nssmic.2015.7582224" @default.
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