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Single-Frame Signal Recovery Using a Similarity-Prior

  • Sakinah A. PitchayEmail author
  • Ata Kabán
Conference paper
  • 2.4k Downloads
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 30)

Abstract

We consider the problem of signal reconstruction from noisy observations in a highly under-determined problem setting. Most of previous work does not consider any specific extra information to recover the signal. Here we address this problem by exploiting the similarity between the signal of interest and a consecutive motionless frame. We incorporate this additional information of similarity that is available into a probabilistic image-prior based on the Pearson type VII Markov Random Field model. Results on both synthetic and real data of MRI images demonstrate the effectiveness of our method in both compressed setting and classical super-resolution experiments.

Keywords

Single-frame super-resolution Compressive sensing Similarity prior Image recovery 

Notes

Acknowledgements

The first author wishes to thank Universiti Sains Islam Malaysia(USIM) and the Ministry of Higher Education of Malaysia (MOHE) for the support and facilities provided. Extended version of the work presented at ICPRAM2012 [1].

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.School of Computer ScienceUniversity of BirminghamBirminghmUK

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