Image denoising based on a mixture of bivariate Laplacian models in complex wavelet domain

Hossein Rabbani, Mansur Vafadust, Ivan Selesnick, Saeed Gazor

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

Abstract

Recently, it has been shown that algorithms exploiting dependencies between coefficients for modeling probability density function (pdf) of wavelet coefficients, could achieve better results for image denoising in wavelet domain compared with the ones based on the independence assumption. In this context, we design a bivariate maximum a posteriori (MAP) estimator which relies on a mixture of bivariate Laplacian models. This model not only is bivariate but also is mixture and therefore, using this new statistical model, we are able to better capture heavy-tailed natures of the data as well as the interscale dependencies of wavelet coefficients. The simulation results show that our proposed technique achieves better performance than several published methods both visually and in terms of peak signal-to-noise ratio (PSNR).

Original languageEnglish (US)
Title of host publication2006 IEEE 8th Workshop on Multimedia Signal Processing, MMSP 2006
Pages425-428
Number of pages4
DOIs
StatePublished - 2007
Event2006 IEEE 8th Workshop on Multimedia Signal Processing, MMSP 2006 - Victoria, BC, Canada
Duration: Oct 3 2006Oct 6 2006

Other

Other2006 IEEE 8th Workshop on Multimedia Signal Processing, MMSP 2006
CountryCanada
CityVictoria, BC
Period10/3/0610/6/06

Fingerprint

Image denoising
Probability density function
Signal to noise ratio
Statistical Models

Keywords

  • Bivariate pdf
  • Complex wavelet transform
  • MAP estimator
  • Mixture model

ASJC Scopus subject areas

  • Signal Processing

Cite this

Rabbani, H., Vafadust, M., Selesnick, I., & Gazor, S. (2007). Image denoising based on a mixture of bivariate Laplacian models in complex wavelet domain. In 2006 IEEE 8th Workshop on Multimedia Signal Processing, MMSP 2006 (pp. 425-428). [4064594] https://doi.org/10.1109/MMSP.2006.285344

Image denoising based on a mixture of bivariate Laplacian models in complex wavelet domain. / Rabbani, Hossein; Vafadust, Mansur; Selesnick, Ivan; Gazor, Saeed.

2006 IEEE 8th Workshop on Multimedia Signal Processing, MMSP 2006. 2007. p. 425-428 4064594.

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

Rabbani, H, Vafadust, M, Selesnick, I & Gazor, S 2007, Image denoising based on a mixture of bivariate Laplacian models in complex wavelet domain. in 2006 IEEE 8th Workshop on Multimedia Signal Processing, MMSP 2006., 4064594, pp. 425-428, 2006 IEEE 8th Workshop on Multimedia Signal Processing, MMSP 2006, Victoria, BC, Canada, 10/3/06. https://doi.org/10.1109/MMSP.2006.285344
Rabbani H, Vafadust M, Selesnick I, Gazor S. Image denoising based on a mixture of bivariate Laplacian models in complex wavelet domain. In 2006 IEEE 8th Workshop on Multimedia Signal Processing, MMSP 2006. 2007. p. 425-428. 4064594 https://doi.org/10.1109/MMSP.2006.285344
Rabbani, Hossein ; Vafadust, Mansur ; Selesnick, Ivan ; Gazor, Saeed. / Image denoising based on a mixture of bivariate Laplacian models in complex wavelet domain. 2006 IEEE 8th Workshop on Multimedia Signal Processing, MMSP 2006. 2007. pp. 425-428
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