Image colorization by fusion of color transfers based on DFT and variance features
| Autor: | Lihua Min, Minling Zheng, Michael K. Ng, Zhengmeng Jin |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Fusion
Efficient algorithm business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition 010103 numerical & computational mathematics Variance (accounting) Non local 01 natural sciences 010101 applied mathematics Computational Mathematics Computational Theory and Mathematics Image colorization Simple (abstract algebra) Modeling and Simulation Convergence (routing) Fuse (electrical) Artificial intelligence 0101 mathematics business Mathematics |
| Zdroj: | Computers & Mathematics with Applications. 77:2553-2567 |
| ISSN: | 0898-1221 |
| Popis: | Color transfer methods usually suffer from spatial color coherency problem. In order to address this problem, this paper develops a fused color transfer method for image colorization. Our idea is to design a local student’s t-test to screen the incoherent colors in the preliminary colorization results obtained by a simple color transfer method with DFT and variance features. Furthermore, we propose a variational fusion model to inpaint these incoherent colors and fuse the other useful colors together. We also present an efficient algorithm for solving the fusion model numerically, and show the convergence of the algorithm. Finally, experimental results are reported to demonstrate the effectiveness of the proposed method, and its performance is competitive with those of the other testing methods. |
| Databáze: | OpenAIRE |
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