Image denoising based on scale-space mixture modeling of wavelet coefficients

Juan Liu, Pierre Moulin

Research output: Contribution to conferencePaper

Abstract

In this paper, we propose a novel hierarchical statistical model for image wavelet coefficients. A simple classification scheme is used to construct a model that captures interscale and intrascale dependencies of wavelet coefficients. Applications to image denoising are presented. We develop a simple algorithm that outperforms other wavelet denoising schemes that exploit first-order statistics, or inter- or intra- scale dependencies alone.

Original languageEnglish (US)
Pages386-390
Number of pages5
StatePublished - Dec 1 1999
EventInternational Conference on Image Processing (ICIP'99) - Kobe, Jpn
Duration: Oct 24 1999Oct 28 1999

Other

OtherInternational Conference on Image Processing (ICIP'99)
CityKobe, Jpn
Period10/24/9910/28/99

Fingerprint

Image denoising
Statistics
Statistical Models

ASJC Scopus subject areas

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

Cite this

Liu, J., & Moulin, P. (1999). Image denoising based on scale-space mixture modeling of wavelet coefficients. 386-390. Paper presented at International Conference on Image Processing (ICIP'99), Kobe, Jpn, .

Image denoising based on scale-space mixture modeling of wavelet coefficients. / Liu, Juan; Moulin, Pierre.

1999. 386-390 Paper presented at International Conference on Image Processing (ICIP'99), Kobe, Jpn, .

Research output: Contribution to conferencePaper

Liu, J & Moulin, P 1999, 'Image denoising based on scale-space mixture modeling of wavelet coefficients' Paper presented at International Conference on Image Processing (ICIP'99), Kobe, Jpn, 10/24/99 - 10/28/99, pp. 386-390.
Liu J, Moulin P. Image denoising based on scale-space mixture modeling of wavelet coefficients. 1999. Paper presented at International Conference on Image Processing (ICIP'99), Kobe, Jpn, .
Liu, Juan ; Moulin, Pierre. / Image denoising based on scale-space mixture modeling of wavelet coefficients. Paper presented at International Conference on Image Processing (ICIP'99), Kobe, Jpn, .5 p.
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