Spatially adaptive high-resolution image reconstruction of low-resolution DCT-based compressed images

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

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

8 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)
StatePublished - 2002
EventInternational Conference on Image Processing (ICIP'02) - Rochester, NY, United States
Duration: Sep 22 2002Sep 25 2002


OtherInternational Conference on Image Processing (ICIP'02)
Country/TerritoryUnited States
CityRochester, NY

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


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