Name
Title | ||
|---|---|---|
Residues cluster-based segmentation and outlier-detection method for large-scale phase unwrapping. |
Abstract | ||
|---|---|---|
2-D phase unwrapping is an important technique in many applications. However, with the growth of image scale, how to tile and splice the image effectively has become a new challenge. In this paper, the phase unwrapping problem is abstracted as solving a large-scale system of inconsistent linear equations. With the difficulties of large-scale phase unwrapping analyzed, L(0)-norm criterion is found to have potentials in efficient image tiling and splicing. Making use of the clustering characteristic of residue distribution, a tiling strategy is proposed for L(0)-norm criterion. Unfortunately, L(0)-norm is an NP-hard problem, which is very difficult to find an exact solution in a polynomial time. In order to effectively solve this problem, equations corresponding to branch cuts of L(0)-norm in the inconsistent equation system mentioned earlier are considered as outliers, and then an outlier-detection-based phase unwrapping method is proposed. Through this method, a highly accurate approximate solution to this NP-hard problem is achieved. A set of experimental results shows that the proposed approach can avoid the inconsistency between local and global phase unwrapping solutions caused by image tiling. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/TIP.2011.2138148 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
optimisation,large scale,$l^{0}$-norm,inconsistent system of equations,norm criterion,2-d phase unwrapping,image segmentation,np-hard problem,outlier-detection-based phase,image scale,residues cluster-based segmentation,large-scale system,efficient image tiling,global phase,inconsistent linear equations,image tiling,residue distribution,phase unwrapping (pu),large-scale phase unwrapping,outlier detection (od),2d phase unwrapping,outlier-detection method,mathematical model,linear equations,outlier detection,np hard problem,system of equations,indexing terms | Anomaly detection,Linear equation,Pattern recognition,Segmentation,Outlier,Image segmentation,Pixel,Artificial intelligence,Cluster analysis,Time complexity,Mathematics | Journal |
Volume | Issue | ISSN |
20 | 10 | 1941-0042 |
Citations | PageRank | References |
8 | 0.55 | 14 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hanwen Yu | 1 | 28 | 6.84 |
| Zhenfang Li | 2 | 103 | 11.78 |
| Zheng Bao | 3 | 1985 | 155.03 |