关键词: 图像分割, 局部熵, 能量泛函, 灰度不均匀, 非凸正则项

Abstract: To overcome the influence of intensity inhomogeneity on image segmentation, an image segmentation algorithm is proposed by energy functional of local entropy in combination with non-convex regularization, which combines global energy terms of CV model and local energy terms of LBF model, and local entropy information and nonconvex regularization are introduced to construct new energy functional. Firstly, global energy functional is employed to obtain coarse segmentation in CV model, which builds local energy functional based on local entropy information to obtain accurately segmentation. Secondly, non-convex regularization serves as another driving force in image evolution to drive curve evolution and preserve edge. This algorithm minimizes this newly constructed energy functional by using level set method and updates the level set function through iteration to complete the curve evolution. Finally, contrast?experimental?results?show that the proposed method?can efficiently and accurately segment intensity inhomogeneity image.

Key words: image segmentation, local entropy, energy functional, intensity inhomogeneity, non-convex regularization