Statistical model-based fusion of noisy multi-band images in the wavelet domain

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Abstract

A new method for multimodal image fusion, based on statistical modelling of wavelet coefficients, is proposed in this paper. The algorithm draws from the weighted average scheme, but incorporates Laplacian bivariate parent-child statistical dependencies. The interscale dependency is brought in the form of shrinkage functions. The proposed method has been shown to perform very well with noisy datasets, outperforming other conventional methods in terms of fusion quality and noise reduction in the fused output
Translated title of the contributionStatistical model-based fusion of noisy multi-band images in the wavelet domain
Original languageEnglish
Title of host publication10th Conference of the International Society of Information Fusion, Quebec, Canada
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1 - 6
Number of pages6
ISBN (Print)9780662458043
DOIs
Publication statusPublished - Jul 2007
Event10th International Conference on Information Fusion - Quebec City, Canada
Duration: 1 Jul 2007 → …

Conference

Conference10th International Conference on Information Fusion
CountryCanada
CityQuebec City
Period1/07/07 → …

Bibliographical note

Rose publication type: Conference contribution

Sponsorship: The authors are grateful to the financial support by the UK MOD Data and Information Fusion Defence Technology Centre, for project 'Applied Multi-dimensional Fusion'.

Terms of use: Copyright © 2007 IEEE. Reprinted from 10th International Conference on Information Fusion, 2007.

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Keywords

  • image fusion
  • statistical modelling
  • multimodal
  • denoising

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