Rotational image deblurring with sparse matrices

Per Christian Hansen, James G. Nagy, Konstantinos Tigkos

Research output: Contribution to journalJournal articleResearchpeer-review


We describe iterative deblurring algorithms that can handle blur caused by a rotation along an arbitrary axis (including the common case of pure rotation). Our algorithms use a sparse-matrix representation of the blurring operation, which allows us to easily handle several different boundary conditions. We also include robust stopping rules for the iterations. The performance of our algorithms is illustrated with examples.
Original languageEnglish
JournalBIT Numerical Mathematics
Issue number3
Pages (from-to)649-671
Number of pages23
Publication statusPublished - 2014


  • Boundary conditions
  • Image deblurring
  • Iterative algorithms
  • Sparse matrices
  • Stopping rules


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