Name
Abstract | ||
|---|---|---|
Three types of mathematical models, i.e., linear interpolation, regression with polynomials and nonlinear neural network, are usually applied to convert color signals from one space to another. Normally neural network model performs slowly with lower robustness, thus we evaluated the performance of the first two models in this paper. We first analyze the principle of different interpolation models, including tirlinear, prism, pyramid and tetrahedron interpolation, and then study the polynomial regression model with different orders, at last the performance of those models are tested during the color conversion for a RGB displays. The experiment results demonstrate that 3D interpolation and regression methods both obtain satisfied results, while the 3D interpolation usually performs very accurately and robustly with enough color samples. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1145/3452940.3452944 | ICITEE |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bangyong Sun | 1 | 0 | 0.34 |
| Zhe Zhao | 2 | 3 | 4.75 |
| Xingyun Zhao | 3 | 0 | 0.34 |
| Ming Ma | 4 | 0 | 0.34 |
| Mengying Yu | 5 | 0 | 0.34 |
| Lingyun Wei | 6 | 0 | 0.34 |