Image denoising employing a mixture of circular symmetric Laplacian models with local parameters in complex wavelet domain

Hossein Rabbani, Mansur Vafadust, Ivan Selesnick, Saeed Gazor

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

Abstract

In this paper, We present a new image denoising algorithm. We assume a mixture of bivariate circular symmetric Laplacian probability density functions (pdfs) where for each wavelet coefficients may have different local parameter. This pdf characterizes simultaneously 1) the heavy-tailed nature, 2) the interscale dependencies of the wavelet coefficients and also 3) the empirically observed correlation between the coefficient amplitudes. We employ this local bivariate mixture model to derive a Bayesian image denoising technique. This proposed pdf, potentially can fits better the statistical properties of the wavelet coefficients than several other existing models. Our simulation results reveal that the proposed denoising method is among the best reported in the literature. This is justified since the accuracy of the employed distribution for noise-free data determines the denoising performance.

Original languageEnglish (US)
Title of host publication2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
Volume1
DOIs
StatePublished - 2007
Event2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07 - Honolulu, HI, United States
Duration: Apr 15 2007Apr 20 2007

Other

Other2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
CountryUnited States
CityHonolulu, HI
Period4/15/074/20/07

Fingerprint

Image denoising
coefficients
Probability density function
probability density functions
simulation

Keywords

  • Circular symmetric Laplacian pdf
  • Complex wavelet transforms
  • MAP estimator
  • Mixture model

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Signal Processing
  • Acoustics and Ultrasonics

Cite this

Rabbani, H., Vafadust, M., Selesnick, I., & Gazor, S. (2007). Image denoising employing a mixture of circular symmetric Laplacian models with local parameters in complex wavelet domain. In 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07 (Vol. 1). [4217202] https://doi.org/10.1109/ICASSP.2007.366030

Image denoising employing a mixture of circular symmetric Laplacian models with local parameters in complex wavelet domain. / Rabbani, Hossein; Vafadust, Mansur; Selesnick, Ivan; Gazor, Saeed.

2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07. Vol. 1 2007. 4217202.

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

Rabbani, H, Vafadust, M, Selesnick, I & Gazor, S 2007, Image denoising employing a mixture of circular symmetric Laplacian models with local parameters in complex wavelet domain. in 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07. vol. 1, 4217202, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07, Honolulu, HI, United States, 4/15/07. https://doi.org/10.1109/ICASSP.2007.366030
Rabbani H, Vafadust M, Selesnick I, Gazor S. Image denoising employing a mixture of circular symmetric Laplacian models with local parameters in complex wavelet domain. In 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07. Vol. 1. 2007. 4217202 https://doi.org/10.1109/ICASSP.2007.366030
Rabbani, Hossein ; Vafadust, Mansur ; Selesnick, Ivan ; Gazor, Saeed. / Image denoising employing a mixture of circular symmetric Laplacian models with local parameters in complex wavelet domain. 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07. Vol. 1 2007.
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