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 contribution||Statistical model-based fusion of noisy multi-band images in the wavelet domain|
|Title of host publication||10th Conference of the International Society of Information Fusion, Quebec, Canada|
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|Pages||1 - 6|
|Number of pages||6|
|Publication status||Published - Jul 2007|
|Event||10th International Conference on Information Fusion - Quebec City, Canada|
Duration: 1 Jul 2007 → …
|Conference||10th International Conference on Information Fusion|
|Period||1/07/07 → …|
Bibliographical noteRose 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'.
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- image fusion
- statistical modelling