A fast algorithm for image super-resolution from blurred observations

Nirmal K. Bose*, Kwok Po NG, Andy C. Yau

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)

Abstract

We study the problem of reconstruction of a high-resolution image from several blurred low-resolution image frames. The image frames consist of blurred, decimated, and noisy versions of a high-resolution image. The high-resolution image is modeled as a Markov random field (MRF), and a maximum a posteriori (MAP) estimation technique is used for the restoration. We show that with the periodic boundary condition, a high-resolution image can be restored efficiently by using fast Fourier transforms. We also apply the preconditioned conjugate gradient method to restore high-resolution images in the aperiodic boundary condition. Computer simulations are given to illustrate the effectiveness of the proposed approach.

Original languageEnglish
Pages (from-to)1-14
Number of pages14
JournalEurasip Journal on Applied Signal Processing
Volume2006
DOIs
Publication statusPublished - 2006

Scopus Subject Areas

  • Signal Processing
  • Hardware and Architecture
  • Electrical and Electronic Engineering

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