Name
Abstract | ||
|---|---|---|
This paper presented a global exemplar-based image completion method for filling large missing or unwanted regions in an image. Based on three proposed completion rules, image completion problem is formulated as a global discrete optimization problem with a well-defined energy function. The energy function can evaluate image consistency globally and is minimized with an expectation-maximization (EM) like algorithm, which considers patch matching and patch synthesis in a unified way. In the algorithm, M step and E step are achieved by sparse patch subspace searching and optimal seam synthesis respectively. The patch subspace is learned with the statistics of geometric transformation relationships of similar patches. Moreover, E step combines image patch synthesis and coherent correction simultaneously. We analyzed the proposed global energy function and optimization method in theory. Simulation comparisons with other state-of-the-art methods show the superiority of our proposed method in ensuring global coherent and avoiding image blurring. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.sigpro.2015.09.031 | Signal Processing |
Keywords | Field | DocType |
image analysis,texture synthesis | Mathematical optimization,Subspace topology,Geometric transformation,Discrete optimization problem,Texture synthesis,Mathematics | Journal |
Volume | Issue | ISSN |
124 | C | 0165-1684 |
Citations | PageRank | References |
0 | 0.34 | 23 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| shiming ge | 1 | 4 | 1.76 |
| Kaixuan Xie | 2 | 6 | 1.80 |
| shuying li | 3 | 0 | 0.34 |
| Rui Yang | 4 | 9 | 2.20 |