Name
Title | ||
|---|---|---|
Non-parametric mixture model with TV spatial regularisation and its dual expectation maximisation algorithm. |
Abstract | ||
|---|---|---|
An image segmentation method based on a non-parametric mixture model together with total variation (TV) regularisation is proposed. The authors use a kernel density estimator as a basic mixture model, which can better separate the non-central distributed data. To enforce its robustness, they integrate the well-known TV regularisation into the statistical method. They use the dual method to efficie... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1049/iet-ipr.2017.1251 | IET Image Processing |
Keywords | Field | DocType |
expectation-maximisation algorithm,image segmentation,Markov processes,medical image processing,statistical analysis | Parametric model,Pattern recognition,Hidden Markov random field,Segmentation,Algorithm,Image segmentation,Robustness (computer science),Artificial intelligence,Real image,Mixture model,Mathematics,Kernel density estimation | Journal |
Volume | Issue | ISSN |
12 | 9 | 1751-9659 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||