Super-resolution using a wavelet-based adaptive Wiener filter

Nabil G. Sadaka, Lina Karam

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

In this paper, a Wavelet-based Adaptive Wiener Filter (WAWF) super-resolution (SR) algorithm is presented. A redundant discrete dyadic wavelet transform (DDWT) is applied to the input sequence to classify the LR frames into subbands of similar contextual information. The similar subbands from each LR frame are registered using subpixel motion and merged on the same HR grid to form HR subbands of similar contextual and statistical information. Then an adaptive Wiener filter approach is applied locally to each subband in order to interpolate the missing information on the HR gird. The weights of the filter are designed using a parametric circularly symmetric statistical model that adapts to the statistics and the spatial proximity of the neighboring wavelet coefficients. Simulation results show that the proposed WAWF SR algorithm results in a superior performance as compared to existing recent SR schemes.

Original languageEnglish (US)
Title of host publication2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
Pages3309-3312
Number of pages4
DOIs
StatePublished - Dec 1 2010
Event2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong
Duration: Sep 26 2010Sep 29 2010

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2010 17th IEEE International Conference on Image Processing, ICIP 2010
CountryHong Kong
CityHong Kong
Period9/26/109/29/10

Keywords

  • Discrete dyadic wavelet transform
  • Super resolution
  • Wiener filter

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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  • Cite this

    Sadaka, N. G., & Karam, L. (2010). Super-resolution using a wavelet-based adaptive Wiener filter. In 2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings (pp. 3309-3312). [5651639] (Proceedings - International Conference on Image Processing, ICIP). https://doi.org/10.1109/ICIP.2010.5651639