Analysis Operator Learning and its Application to Image Reconstruction

@article{Hawe2013AnalysisOL,
  title={Analysis Operator Learning and its Application to Image Reconstruction},
  author={S. Hawe and M. Kleinsteuber and K. Diepold},
  journal={IEEE Transactions on Image Processing},
  year={2013},
  volume={22},
  pages={2138-2150}
}
  • S. Hawe, M. Kleinsteuber, K. Diepold
  • Published 2013
  • Computer Science, Mathematics, Medicine
  • IEEE Transactions on Image Processing
  • Exploiting a priori known structural information lies at the core of many image reconstruction methods that can be stated as inverse problems. The synthesis model, which assumes that images can be decomposed into a linear combination of very few atoms of some dictionary, is now a well established tool for the design of image reconstruction algorithms. An interesting alternative is the analysis model, where the signal is multiplied by an analysis operator and the outcome is assumed to be sparse… CONTINUE READING
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