A Multi-phase Soft Segmentation Based on Bi-direction Projected PDHG Method
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Summary
A multiphase soft segmentation model for nearly piecewise constant images based on stochastic principle, where intensities of the image are modeled as random variables with mixed Gaussian distribution is proposed.
- Type
- article
- Published
- 2010-01-01
- Cited by
- 0
- References
- 25
- OpenAlex
- https://openalex.org/W122076626
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:7867768
Keywords
Segmentation, Phase (matter), Computer science, Artificial intelligence, Computer vision
References
- Convex Formulation and Exact Global Solutions for Multi-phase Piecewise Constant Mumford-Shah Image Segmentation
- A Variational Level Set Approach to Segmentation and Bias Correction of Images with Intensity Inhomogeneity
- A Fast Total Variation Minimization Method for Image Restoration
- A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters
- On the Convergence of Primal–Dual Hybrid Gradient Algorithms for Total Variation Image Restoration
- A Convergence Theorem for the Fuzzy ISODATA Clustering Algorithms
- Affine Invariant Flows in the Beltrami Framework
- A Stochastic-Variational Model for Soft Mumford-Shah Segmentation
- Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models
- Global Minimization for Continuous Multiphase Partitioning Problems Using a Dual Approach
- Adaptive fuzzy c-means algorithm for image segmentation in the presence of intensity inhomogeneities
- Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
- Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure
- A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data
- Variational Segmentation using Fuzzy Region Competition and Local Non-Parametric Probability Density Functions
- Fast Global Minimization of the Active Contour/Snake Model
- Adaptive Segmentation of MRI Data
- An adaptive fuzzy C-means algorithm for image segmentation in the presence of intensity inhomogeneities
- Active contours without edges
- An Efficient Primal-Dual Hybrid Gradient Algorithm For Total Variation Image Restoration
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