Name
Abstract | ||
|---|---|---|
A multiframe super-resolution (SR) reconstruction algorithm based on cycle-spinning (CS) is proposed. We utilize the relative motion information of sequential images to construct a CS-based framework for the resolution enhancement. The unique feature of the proposed algorithm is that it is effective for low-resolution (LR) images with various point spread function (PSF) and noise characteristics, even if the degradation models are unknown for the imaging system. Moreover, the computational complexity is inexpensive. Experiments demonstrate the effectiveness of the proposed method and show the superiority to previous methods in objective and subjective qualities. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ICASSP.2007.365968 | ICASSP (1) |
Keywords | Field | DocType |
relative motion information,noise characteristics,point spread function,image resolution,cycle-spinning,cycle-spinning methods,image reconstruction,computational complexity,image sequence,super-resolution,image sequences,multiframe superresolution reconstruction algorithm,degradation models,resolution enhancement,image enhancement,multiframe,image motion analysis,iterative methods,degradation,interpolation,noise reduction,frequency,strontium,spatial resolution,low resolution,super resolution | Iterative reconstruction,Computer vision,Spinning,Computer science,Relative motion,Reconstruction algorithm,Artificial intelligence,Point spread function,Superresolution,Image resolution,Computational complexity theory | Conference |
Volume | ISSN | ISBN |
1 | 1520-6149 | 1-4244-0727-3 |
Citations | PageRank | References |
0 | 0.34 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yan Cheng | 1 | 0 | 0.34 |
| Xiangzhong Fang | 2 | 147 | 21.63 |
| Jun Hou | 3 | 4 | 1.79 |
| Yu Song | 4 | 356 | 52.74 |