The problem of recovering a high-resolution image from a sequence of low-resolution DCT-based compressed images is considered in this paper. The presence of the compression system complicates the recovery problem, as the operation reduces the amount of frequency aliasing in the low-resolution frames and introduces a non-linear quantization process. The effect of the quantization error and resulting inaccurate sub-pixel motion information is modeled as a zero-mean additive correlated Gaussian noise. A regularization functional is introduced not only to reflect the relative amount of registration error in each low-resolution image but also to determine the regularization parameter without any prior knowledge in the reconstruction procedure. The effectiveness of the proposed algorithm is demonstrated experimentally.
|Original language||English (US)|
|Number of pages||4|
|Journal||ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings|
|State||Published - Jan 1 2002|
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering