Super-resolution image processing algorithm using hybrid up-sampling

Jong Hyun Park, Moon Gi Kang

Research output: Contribution to journalArticlepeer-review


In this paper, we present a new image up-sampling method which registers low resolution images to the high resolution grid when Bayesian super-resolution image processing is performed. The proposed up-sampling method interpolates high-resolution pixels using high-frequency data lying in all the low resolution images, instead of up-sampling each low resolution image separately. The interpolation is based on B-spline non-uniform re-sampling, adjusted for the super-resolution image processing. The experimental results demonstrate the effects when different up-sampling methods generally used such as zero-padding or bilinear interpolation are applied to the super-resolution image reconstruction. Then, we show that the proposed hybird up-sampling method generates high-resolution images more accurately than conventional methods with quantitative and qualitative assess measures.

Original languageEnglish
Pages (from-to)294-302
Number of pages9
JournalTransactions of the Korean Institute of Electrical Engineers
Issue number2
Publication statusPublished - 2008 Feb

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering


Dive into the research topics of 'Super-resolution image processing algorithm using hybrid up-sampling'. Together they form a unique fingerprint.

Cite this