Inpainting with sparse linear combinations of exemplars

  • Authors:
  • Brendt Wohlberg

  • Affiliations:
  • T-7 Mathematical Modeling and Analysis, Los Alamos National Laboratory, NM 87545, USA

  • Venue:
  • ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
  • Year:
  • 2009

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Abstract

We introduce a new exemplar-based inpainting algorithm that represents the region to be inpainted as a sparse linear combination of example blocks, extracted from the image being inpainted or an external training image set. This method is conceptually simple, being computed by minimization of a simple functional, and avoids the complexity of correctly ordering the filling in of missing regions of other exemplar-based methods. Initial performance comparisons on small inpainting regions indicate that this method provides similar or better performance than other recent methods.