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An Evaluation of Potential Functions for Regularized Image Deblurring

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Image Analysis and Recognition (ICIAR 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8814))

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Abstract

We explore utilization of seven different potential functions in restoration of images degraded by both noise and blur. Spectral Projected Gradient method confirms its excellent performance in terms of speed and flexibility for optimization of complex energy functions. Results obtained on images affected by different levels of Gaussian noise and different sizes of the Point Spread Functions, are presented. The Huber potential function demonstrates outstanding performance.

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Author information

Authors and Affiliations

  1. Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia

    Buda Bajić, Joakim Lindblad & Nataša Sladoje

  2. Centre for Image Analysis, Uppsala University, Uppsala, Sweden

    Nataša Sladoje

Authors
  1. Buda Bajić
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  2. Joakim Lindblad
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  3. Nataša Sladoje
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Corresponding author

Correspondence to Buda Bajić .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Porto, Porto, Portugal

    Aurélio Campilho

  2. Dept. of Electrical and Computer Eng., University of Waterloo, Waterloo, Ontario, Canada

    Mohamed Kamel

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© 2014 Springer International Publishing Switzerland

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Bajić, B., Lindblad, J., Sladoje, N. (2014). An Evaluation of Potential Functions for Regularized Image Deblurring. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2014. Lecture Notes in Computer Science(), vol 8814. Springer, Cham. https://doi.org/10.1007/978-3-319-11758-4_17

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  • DOI: https://doi.org/10.1007/978-3-319-11758-4_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11757-7

  • Online ISBN: 978-3-319-11758-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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