A Nonlinear L1-Norm Approach for Joint Image Registration and Super-Resolution

Kim Hui Yap, Yu He, Yushuang Tian, Lap Pui Chau

Research output: Journal article publicationJournal articleAcademic researchpeer-review

22 Citations (Scopus)


This letter proposes a nonlinear L1-norm approach for joint image registration and super-resolution (SR). Image SR is the fusion of multiple low-resolution (LR) images to produce a high-resolution (HR) image. Conventional SR algorithms are sensitive to the initial registration error and outliers in the LR images. In view of this, we present a new SR method to address these problems using L1-norm optimization in joint image registration and HR image reconstruction. Experimental results show that the proposed method is effective in handling these issues in the HR image reconstruction.

Original languageEnglish
Pages (from-to)981-984
Number of pages4
JournalIEEE Signal Processing Letters
Issue number11
Publication statusPublished - Nov 2009
Externally publishedYes


  • Image registration
  • image super-resolution
  • L-norm
  • nonlinear algorithm

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics


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