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Intensity inhomogeneities often occur in real-world images and may cause considerable difficulties in image segmentation. In order to overcome the difficulties caused by intensity inhomogeneities, we propose a region-based active contour model that draws upon intensity information in local regions at a controllable scale. A data fitting energy is defined in(More)
We propose a convex image segmentation model in a variational level set formulation. Both the local information and the global information are taken into consideration to get better segmentation results.We first propose a globally convex energy functional to combine the local and global intensity fitting terms. The proposed energy functional is then(More)
Static video summarization is recognized as an effective way for users to quickly browse and comprehend large numbers of videos. In this paper, we formulate static video summarization as a clustering problem. Inspired by the idea from high density peaks search clustering algorithm, we propose an effective clustering algorithm by integrating important(More)
This paper presents an improved active contour model for fast multiphase image segmentation based on the piecewise constant Vese-Chan model and the split Bregman method. We first define a new energy functional by applying the globally convex image segmentation technique to the Vese-Chan energy functional and incorporating the edge information with a(More)
With the rapid development of medical imaging technology, the image segmentation has a special significance in medical applications. It's known that intensity inhomogeneity is one of the important features of magnetic resonance (MR) images, which presents a quite challenge in MRI segmentation. In this paper the authors apply the split Bregman method for(More)