Image restoration using Gaussian scale mixtures in the wavelet domain

Javier Portilla, Eero Simoncelli

Research output: Contribution to conferencePaper

Abstract

We describe a statistical model for images decomposed in an overcomplete wavelet pyramid. Each neighborhood of pyramid coefficients is modeled as the product of a Gaussian vector of known covariance, and an independent hidden positive scalar random variable. We propose an efficient Bayesian estimator for the pyramid coefficients of an image degraded by linear distortion (e.g., blur) and additive Gaussian noise. We demonstrate the quality of our results in simulations over a wide range of blur and noise levels.

Original languageEnglish (US)
Pages965-968
Number of pages4
StatePublished - Dec 17 2003
EventProceedings: 2003 International Conference on Image Processing, ICIP-2003 - Barcelona, Spain
Duration: Sep 14 2003Sep 17 2003

Other

OtherProceedings: 2003 International Conference on Image Processing, ICIP-2003
CountrySpain
CityBarcelona
Period9/14/039/17/03

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ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

Cite this

Portilla, J., & Simoncelli, E. (2003). Image restoration using Gaussian scale mixtures in the wavelet domain. 965-968. Paper presented at Proceedings: 2003 International Conference on Image Processing, ICIP-2003, Barcelona, Spain.