Statistical image restoration based on adaptive wavelet models

Research output: Contribution to conferencePaper

Abstract

In this paper, we propose image restoration algorithms based on adaptive wavelet-domain statistical models. We present a method to estimate the model parameters from the observations, and solve the restoration problem in orthonormal and translation-invariant wavelet domains. Substantial improvements over previous wavelet-based restoration methods are obtained. The use of a translation-invariant basis further enhances the restoration performance.

Original languageEnglish (US)
Pages21-24
Number of pages4
StatePublished - Jan 1 2001
EventIEEE International Conference on Image Processing (ICIP) - Thessaloniki, Greece
Duration: Oct 7 2001Oct 10 2001

Other

OtherIEEE International Conference on Image Processing (ICIP)
CountryGreece
CityThessaloniki
Period10/7/0110/10/01

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ASJC Scopus subject areas

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

Cite this

Liu, J., & Moulin, P. (2001). Statistical image restoration based on adaptive wavelet models. 21-24. Paper presented at IEEE International Conference on Image Processing (ICIP), Thessaloniki, Greece.