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Title
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Wavelet-based EM algorithm for multispectral-image restoration
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Author
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Abstract
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| In this paper, we present a technique for the restoration of multispectral images. The presented procedure is based on an expectation-maximization (EM) algorithm, which applies iteratively a deconvolution and a denoising step. The restoration is performed in a multispectral way instead of band-by-band. The deconvolution technique is a generalization of the EM-based grayscale-image restoration and allows for the reconstruction of spatial as well as spectral blurring. The denoising step is performed in wavelet domain. To account for interband correlations, a multispectral probability density model for the wavelet coefficients is chosen. Rather than using a multinormal model, we opted for a Gaussian scale mixture model, which is a heavy-tailed model. Also in this paper, the framework is extended to include an auxiliary image of the same scene to improve the restoration. Experiments on Landsat and AVIRIS multispectral remote-sensing images are conducted. |
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Language
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English
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Source (journal)
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IEEE transactions on geoscience and remote sensing / Institute of Electrical and Electronics Engineers [New York, N.Y.] - New York, N.Y., 1980, currens
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Publication
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New York, N.Y.
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2009
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ISSN
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0196-2892
[print]
1558-0644
[online]
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DOI
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10.1109/TGRS.2009.2031103
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Volume/pages
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47
:11
(2009)
, p. 3892-3898
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ISI
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000271140400029
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Full text (Publisher's DOI)
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