High-resolution image reconstruction of low-resolution DCT-based compressed images

Sung Cheol Park, Moon Gi Kang, C. Andrew Segall, Aggelos K. Katsaggelos

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


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 languageEnglish (US)
Pages (from-to)1665-1668
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
StatePublished - 2002

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering


Dive into the research topics of 'High-resolution image reconstruction of low-resolution DCT-based compressed images'. Together they form a unique fingerprint.

Cite this