A Novel Euler’s Elastica-Based Segmentation Approach for Noisy Images Using the Progressive Hedging Algorithm
Euler’s elastica-based unsupervised segmentation models have strong capability of completing the missing boundaries for existing objects in a clean image, but they are not working well for noisy images. This paper aims to establish a Euler’s elastica-based approach that can properly deal with the ra...
| Main Authors: | Tan, Lu, Li, Ling, Liu, Wan-Quan, Sun, Jie, Zhang, M. |
|---|---|
| Format: | Journal Article |
| Language: | English |
| Published: |
SPRINGER
2020
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/91437 |
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