Super Resolution Based on Scale Invariant Feature Transform
In this paper, SIFT (scale invariant feature transform) algorithm is used for the image registration of super resolution to ensure a more stable and accurate registration result, and thus improve the result of super-resolution which will be realized by least squares minimization. The advantage of this approach is that the super-resolution process will have a stable result even under severe transformation conditions. SIFT method is compared with Kerens method to prove its accuracy and robustness. Fine reconstruction results are also given to show the effectiveness of this approach. Simultaneous registration method can be introduced in future work to further improve the registration accuracy.
Zhi Yuan Peimin Yan Sheng Li
School of Communication and Information Engineering Shanghai University, Shanghai200072, P.R.China
国际会议
2008 International Conference on Audio，Language and Image Processing(2008国际声音、语言、图像过程大会)
镇江
英文
1550-1554
2008-07-07（万方平台首次上网日期，不代表论文的发表时间）