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• W1970321438 abstract "The soft additive segmentation model attempts to solve the problem related to the segmentation of overlapping objects with additive intensity value. An issue in optimizing the soft additive segmentation functional is that a high-order nonlinear partial differential equation needs to be solved, which, for most standard algorithms, involves high computational cost. In this paper, we propose a fast and efficient numerical algorithm to optimize the soft additive segmentation model. We reformulate the original minimization problem into a sequence of simpler minimization problems that can be solved efficiently by using the augmented Lagrangian method. Numerical tests on real and synthetic cases are presented to demonstrate the efficiency of our algorithm." @default.
• W1970321438 created "2016-06-24" @default.
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• W1970321438 date "2012-01-01" @default.
• W1970321438 modified "2023-09-24" @default.
• W1970321438 title "A Fast Method for Segmenting Images with Additive Intensity Value" @default.
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• W1970321438 doi "https://doi.org/10.1137/120863617" @default.
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