A Novel Variational Model and Its Fast Algorithm for Noisy Image Segmentation
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Abstract
A new variational model for segmenting the images corrupted by various noise is proposed.Firstly,the energy function of the presented model based on Chan-Vese model is modified,and a new auxiliary variable is introduced to integrate some fitting terms.Secondly,it is extended to convex optimization by convex relaxation.And the solution is decomposed into solving a few functional optimization sub-problems,which can be obtained by applying Split-Bregman algorithm and additive operator splitting(AOS) numerical algorithm,the effective results are obtained.Comparing with the model in which a auxiliary variable is not introduced,experimental results verify that the proposed model for segmenting the noisy images reduce computational time and has better results.
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