Name
Abstract | ||
|---|---|---|
In this paper, we propose a new interpolation-based method of image super-resolution reconstruction. The idea is using multisurface fitting to take full advantage of spatial structure information. Each site of low-resolution pixels is fitted with one surface, and the final estimation is made by fusing the multisampling values on these surfaces in the maximum a posteriori fashion. With this method, the reconstructed high-resolution images preserve image details effectively without any hypothesis on image prior. Furthermore, we extend our method to a more general noise model. Experimental results on the simulated and real-world data show the superiority of the proposed method in both quantitative and visual comparisons. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/TIP.2012.2189576 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
Data fusion,multisurface fitting,nonuniform interpolation,super-resolution (SR) | Iterative reconstruction,Computer vision,Pattern recognition,Interpolation,Sensor fusion,Artificial intelligence,Pixel,Maximum a posteriori estimation,Spatial structure,Image resolution,Superresolution,Mathematics | Journal |
Volume | Issue | ISSN |
21 | 7 | 1941-0042 |
Citations | PageRank | References |
26 | 0.80 | 15 |
Authors | ||
3 | ||