Name
Abstract | ||
|---|---|---|
Concomitant with the increasing demand for high-resolution images, research is actively being conducted into the temporal and spatial estimation of high-resolution images from transmitted low-resolution images via high-capacity, high-speed facilities such as the cloud, to rectify traffic efficiency problems that arise while transmitting images across networks. This paper proposes a double linear---cubic convolution interpolation, without a weighted operator, for spatial resolution enhancement. The proposed method is a combination of the existing linear interpolation method and the cubic convolution interpolation method, with the weight coefficient generator used in conventional interpolation methods removed to reduce hardware usage. Experimental results indicate that the proposed interpolation method has a lower complexity, provides better peak signal-to-noise ratio and structural similarity, and uses less hardware resources than bicubic convolution interpolation. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/s11227-017-1988-8 | The Journal of Supercomputing |
Keywords | Field | DocType |
Resolution up-conversion,Mobile cloud,Linear interpolation,Cubic convolution interpolation,VLSI | Nearest-neighbor interpolation,Computer science,Interpolation,Artificial intelligence,Linear interpolation,Trilinear interpolation,Computer vision,Multivariate interpolation,Parallel computing,Bicubic interpolation,Algorithm,Stairstep interpolation,Bilinear interpolation | Journal |
Volume | Issue | ISSN |
73 | 7 | 0920-8542 |
Citations | PageRank | References |
1 | 0.38 | 14 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hae-Min Moon | 1 | 37 | 7.49 |
| Changho Seo | 2 | 90 | 19.36 |
| Sung Bum Pan | 3 | 162 | 36.88 |