A Level Set Approach to Image Segmentation With Intensity Inhomogeneity

8 years 16 days ago

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—It is often a difﬁcult task to accurately segment images with intensity inhomogeneity, because most of representative algorithms are region-based that depend on intensity homogeneity of the interested object. In this paper, we present a novel level set method for image segmentation in the presence of intensity inhomogeneity. The inhomogeneous objects are modeled as Gaussian distributions of different means and variances in which a sliding window is used to map the original image into another domain, where the intensity distribution of each object is still Gaussian but better separated. The means of the Gaussian distributions in the transformed domain can be adaptively estimated by multiplying a bias ﬁeld with the original signal within the window. A maximum likelihood energy functional is then deﬁned on the whole image region, which combines the bias ﬁeld, the level set function, and the piecewise constant function approximating the true image signal. The proposed level set ...

Kaihua Zhang, Lei Zhang, Kin-Man Lam, David Zhang

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