Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10360242 | Image and Vision Computing | 2005 | 12 Pages |
Abstract
Novel theoretical results for the super-resolution reconstruction (SRR) are presented under the case of arbitrary image warping. The SRR model is reasonably separated into two parts of anti-aliasing and deblurring. The anti-aliasing part is proved to be well-posed. The ill-posedness of the entire SRR process is shown to be mainly caused by the deblurring part. The motion estimation error results in a multiplicative perturbation to the warping matrix, and the perturbation bound is derived. The common regularization algorithms used in SRR are analyzed through the discrete Picard condition, which provides a theoretical measure for limits on SRR. Experiments and examples are supplied to validate the presented theories.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Zhaozhong Wang, Feihu Qi,