Image Fusion using additive multirresolution wavelets decomposition image merging. Applications to SPOT + LANDSAT images
A technique based on multiresolution wavelet decomposition was developed for the merging and data fusion of a high-resolution panchromatic image and a low-resolution multispectral image. The standard data fusion methods may not be satisfactory, because they can distort the spectral characteristics o...
| Authors: | , , , , , |
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| Format: | article |
| Status: | Published version |
| Publication Date: | 1999 |
| Country: | España |
| Institution: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repository: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:2445/218460 |
| Online Access: | https://hdl.handle.net/2445/218460 |
| Access Level: | Open access |
| Keyword: | Ondetes (Matemàtica) Imatges satel·litàries Satèl·lits Wavelets (Mathematics) Remote-sensing images Satellites |
| Summary: | A technique based on multiresolution wavelet decomposition was developed for the merging and data fusion of a high-resolution panchromatic image and a low-resolution multispectral image. The standard data fusion methods may not be satisfactory, because they can distort the spectral characteristics of the multispectral data. The method presented here consists of adding the wavelet coefficients of the high-resolution image to the multispectral (low-resolution) data. More specifically, we add the high-order coefficients of the wavelet transform of the panchromatic image to the intensity component (L) of the multispectral image. The method is thus an improvement on standard intensity–hue–saturation (IHS or LHS) mergers. An alternative approach for correcting the red–green–blue coefficients is also discussed. We used the method to merge SPOT and Landsat Thematic Mapper images (SPOT means Système pour l’Observation de la Terre). The technique presented is clearly better than the IHS and LHS mergers for preserving both spectral and spatial information. |
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