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19 January 2001 Improving wavelet-based merging of panchromatic and multispectral images by contextual information
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Low-level, or pixel-based, fusion tends to use efficiently the information data acquired by sensors having different spatial and radiometric resolutions. Several methods have been proposed for merging panchromatic and multispectral data. Recently, multiresolution analysis has become one of the most promising methods for the analysis of remote sensing images. The use of the wavelet “à trous” algorithm allows to apply a dyadic wavelet to merge nondyadic data, by using a stationary or redundant transform, for which decimation is not carried out. The high-resolution coefficients of the image having high spatial resolution, may be added to the luminance component of the multispectral data. This procedure, namely AWL, which starts from a redundant bandpass representation of the image data, is very appealing, because the spectral quality is obviously highly preserved. However, it may suffer from a non-uniform spatial enhancement of the multispectral bands. In this paper, a method is proposed which uses spatial local information on the wavelet planes obtained from the “à trous” wavelet decomposition. The paper aims to improve the additive method by incorporating contextual spatial information to reduce possible overenhancement of the multispectral data in the image regions having higher spectral content, e.g., in highly textured regions.
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Andrea Garzelli, Giuliano Benelli, Mauro Barni, and C. Magini "Improving wavelet-based merging of panchromatic and multispectral images by contextual information", Proc. SPIE 4170, Image and Signal Processing for Remote Sensing VI, (19 January 2001);

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